Triple
T11114496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avokaya language |
E262848
|
entity |
| Predicate | hasNeighboringLanguage |
P16383
|
FINISHED |
| Object |
Logo language
Logo is a Central Sudanic language spoken in parts of South Sudan and the Democratic Republic of the Congo.
|
E905152
|
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: Logo language | Statement: [Avokaya language, hasNeighboringLanguage, Logo language]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Logo language Context triple: [Avokaya language, hasNeighboringLanguage, Logo language]
-
A.
Lingo
Lingo is a scripting language primarily known for powering interactive multimedia applications and games in Adobe (formerly Macromedia) Director.
-
B.
For language
For language is an alternative name for the Fur language, a Nilo-Saharan language spoken primarily by the Fur people of western Sudan.
-
C.
Lawangan language
The Lawangan language is an Austronesian language spoken by the Lawangan people of central Kalimantan in Indonesia.
-
D.
Puma language
Puma language is a Kiranti language of the Sino-Tibetan family spoken by the Puma people of eastern Nepal.
-
E.
Lang
Lang is a common Scottish surname borne by numerous notable figures across literature, politics, and other fields.
- 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: Logo language Triple: [Avokaya language, hasNeighboringLanguage, Logo language]
Generated description
Logo is a Central Sudanic language spoken in parts of South Sudan and the Democratic Republic of the Congo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Logo language Target entity description: Logo is a Central Sudanic language spoken in parts of South Sudan and the Democratic Republic of the Congo.
-
A.
Lingo
Lingo is a scripting language primarily known for powering interactive multimedia applications and games in Adobe (formerly Macromedia) Director.
-
B.
For language
For language is an alternative name for the Fur language, a Nilo-Saharan language spoken primarily by the Fur people of western Sudan.
-
C.
Lawangan language
The Lawangan language is an Austronesian language spoken by the Lawangan people of central Kalimantan in Indonesia.
-
D.
Puma language
Puma language is a Kiranti language of the Sino-Tibetan family spoken by the Puma people of eastern Nepal.
-
E.
Lang
Lang is a common Scottish surname borne by numerous notable figures across literature, politics, and other fields.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d79aa637888190935e852281408356 |
completed | April 9, 2026, 12:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e42d7da99881908d38ea66c37dfb92 |
completed | April 19, 2026, 1:18 a.m. |
| NEDg | Description generation | batch_69e42e67724481908bd9e73487a80d44 |
completed | April 19, 2026, 1:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e4308103c48190b32ee3047d9a0860 |
completed | April 19, 2026, 1:31 a.m. |
Created at: April 8, 2026, 9:27 p.m.