Triple
T5161222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tsévié |
E116440
|
entity |
| Predicate | distanceToLomé |
P61860
|
FINISHED |
| Object | about 35 kilometres |
—
|
LITERAL 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: about 35 kilometres | Statement: [Tsévié, distanceToLomé, about 35 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToLomé Context triple: [Tsévié, distanceToLomé, about 35 kilometres]
-
A.
distanceToPort-au-Prince
Indicates the spatial distance between a given location and the city of Port-au-Prince.
-
B.
distanceFromDakar
Indicates the spatial distance between a given entity’s location and the city of Dakar.
-
C.
distanceFromPortOfSpain
Indicates the measured distance between a given location and the city of Port of Spain.
-
D.
distanceToHoniaraApprox
Indicates an approximate distance measurement between a given entity’s location and the location of Honiara.
-
E.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
- F. None of above. chosen
Provenance (4 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_69bd445edb3881909b93b34d260717fc |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79073a54819080cd1e8de6fe906a |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77b36c008190b91011a9fa52b3d2 |
completed | March 20, 2026, 4:37 p.m. |
| PDg | Predicate description generation | batch_69bd78d6a1388190804dcf568ca92129 |
completed | March 20, 2026, 4:41 p.m. |
Created at: March 20, 2026, 1:44 p.m.