Triple
T2755682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fula language |
E61093
|
entity |
| Predicate | hasAlternativeName |
P39
|
FINISHED |
| Object | Pular |
E289566
|
NE FINISHED |
How this triple was built (2 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: Pular | Statement: [Fula language, hasAlternativeName, Pular]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pular Context triple: [Fula language, hasAlternativeName, Pular]
-
A.
Pular
chosen
Pular is a major variety of the Fula (Fulfulde) language spoken primarily in Guinea and neighboring West African countries.
-
B.
Passabe
Passabe is a village and administrative post in the Oecusse exclave of Timor-Leste, known for its remote location and its role in the region’s political and social history.
-
C.
Hurdle
Hurdle is a surname most notably associated with Clint Hurdle, a former Major League Baseball player and manager.
-
D.
Ponto de Parada
Ponto de Parada is a neighborhood in the city of Recife, Brazil, known primarily as a residential area within the metropolitan region.
-
E.
Pounce
Pounce is the costumed panther mascot representing Georgia State University at its athletic events and campus activities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ab4b7a85bc819094a349b84beb1f2c |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb718f4c8190bfc34c6597163ebc |
completed | March 7, 2026, 8:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afbbdd509c8190ac62aa6d50dea3a6 |
completed | March 10, 2026, 6:36 a.m. |
Created at: March 6, 2026, 9:56 p.m.