Triple
T10653097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Order of Luthuli |
E251021
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
OL
OL is the official abbreviation for the Order of Luthuli, a South African national honor awarded for exceptional contributions to democracy, human rights, and nation-building.
|
E877359
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: OL | Statement: [Order of Luthuli, abbreviation, OL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: OL Context triple: [Order of Luthuli, abbreviation, OL]
-
A.
OL
OL is a UK postcode area covering Oldham and surrounding parts of Greater Manchester and nearby regions in North West England.
-
B.
OL
OL is the commonly used abbreviation for Olympique Lyonnais, a major French football club best known internationally for its highly successful women's team.
-
C.
OL
OL is the vehicle registration code for the city of Oldenburg in the German state of Lower Saxony.
-
D.
OL
OL is the post-nominal abbreviation used by recipients of Papua New Guinea’s Order of Logohu, a national honor recognizing distinguished service.
-
E.
OLE
OLE (Object Linking and Embedding) is a Microsoft technology that enables embedding and linking to documents and other objects within different applications, forming a foundation for later component technologies like ActiveX.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: OL Triple: [Order of Luthuli, abbreviation, OL]
Generated description
OL is the official abbreviation for the Order of Luthuli, a South African national honor awarded for exceptional contributions to democracy, human rights, and nation-building.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: OL Target entity description: OL is the official abbreviation for the Order of Luthuli, a South African national honor awarded for exceptional contributions to democracy, human rights, and nation-building.
-
A.
OL
OL is a UK postcode area covering Oldham and surrounding parts of Greater Manchester and nearby regions in North West England.
-
B.
OL
OL is the commonly used abbreviation for Olympique Lyonnais, a major French football club best known internationally for its highly successful women's team.
-
C.
OL
OL is the vehicle registration code for the city of Oldenburg in the German state of Lower Saxony.
-
D.
OL
OL is the post-nominal abbreviation used by recipients of Papua New Guinea’s Order of Logohu, a national honor recognizing distinguished service.
-
E.
OLE
OLE (Object Linking and Embedding) is a Microsoft technology that enables embedding and linking to documents and other objects within different applications, forming a foundation for later component technologies like ActiveX.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6aa5a4c4881908f39be6efe5981e5 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6dff78ec88190a4d1863fe87245f6 |
completed | April 8, 2026, 11:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d97a71fac48190a6d7c99ebc5aad0a |
completed | April 10, 2026, 10:32 p.m. |
| NEDg | Description generation | batch_69d97cc2b66c8190909a23927fbe3af5 |
completed | April 10, 2026, 10:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d97e13913081908dd1fb60fa44db05 |
completed | April 10, 2026, 10:47 p.m. |
Created at: April 8, 2026, 9:06 p.m.