Triple
T6840468
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Slessor |
E157559
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Slessor
Slessor is a Scottish-origin surname borne by several notable figures, including military leaders and missionaries.
|
E623781
|
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: Slessor | Statement: [John Slessor, familyName, Slessor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slessor Context triple: [John Slessor, familyName, Slessor]
-
A.
Russell Hill
Russell Hill is a locality in Canberra, Australia, situated close to the parliamentary precinct of Capital Hill.
-
B.
Lionel Hall
Lionel Hall is an undergraduate dormitory building located within Harvard University's historic Harvard Yard.
-
C.
S. R. Crown
S. R. Crown was a benefactor whose support and patronage were honored through the naming of the iconic modernist building Crown Hall at the Illinois Institute of Technology.
-
D.
Martin Lisemore
Martin Lisemore was a British television producer best known for his acclaimed work on high-profile BBC drama series in the 1970s.
-
E.
Neil Smith
Neil Smith is a film editor known for his work on major feature films, including the fantasy action movie "Snow White and the Huntsman."
- 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: Slessor Triple: [John Slessor, familyName, Slessor]
Generated description
Slessor is a Scottish-origin surname borne by several notable figures, including military leaders and missionaries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Slessor Target entity description: Slessor is a Scottish-origin surname borne by several notable figures, including military leaders and missionaries.
-
A.
Russell Hill
Russell Hill is a locality in Canberra, Australia, situated close to the parliamentary precinct of Capital Hill.
-
B.
Lionel Hall
Lionel Hall is an undergraduate dormitory building located within Harvard University's historic Harvard Yard.
-
C.
S. R. Crown
S. R. Crown was a benefactor whose support and patronage were honored through the naming of the iconic modernist building Crown Hall at the Illinois Institute of Technology.
-
D.
Martin Lisemore
Martin Lisemore was a British television producer best known for his acclaimed work on high-profile BBC drama series in the 1970s.
-
E.
Neil Smith
Neil Smith is a film editor known for his work on major feature films, including the fantasy action movie "Snow White and the Huntsman."
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6b2ee248190991c3e827be75bb7 |
completed | March 27, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fb4f80081908198c8270633d34a |
completed | March 28, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69c730cdb3c88190802ddda15d8aa52f |
completed | March 28, 2026, 1:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c734876ca0819087842bec6e01c02e |
completed | March 28, 2026, 1:53 a.m. |
Created at: March 27, 2026, 2:19 p.m.