Triple
T31834241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gentilly |
E812622
|
entity |
| Predicate | distanceToCenterOfParis_km |
P10703
|
FINISHED |
| Object | approximately 4 |
—
|
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: approximately 4 | Statement: [Gentilly, distanceToCenterOfParis_km, approximately 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToCenterOfParis_km Context triple: [Gentilly, distanceToCenterOfParis_km, approximately 4]
-
A.
distanceFromParisCenter
chosen
Indicates the measured distance between a given location and the central point of Paris.
-
B.
distanceToBordeauxCenter
Indicates the measured or calculated distance between a given entity’s location and the center of Bordeaux.
-
C.
distanceFromParisSaintLazare
Indicates the physical distance between a given place and Paris Saint-Lazare railway station.
-
D.
distanceFromParisGareDeLyon
Indicates the distance between an entity and Paris Gare de Lyon railway station.
-
E.
distanceFromFoixKilometres
Indicates the physical distance, measured in kilometers, between a given place or entity and the location of Foix.
- F. None of above.
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_69f348ea7ffc8190a2ab43d80277cf59 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a0235be932081908857bc3a77c27e7d |
completed | May 11, 2026, 8:02 p.m. |
| PD | Predicate disambiguation | batch_6a022c865dec81909e02b2f330e987e6 |
completed | May 11, 2026, 7:22 p.m. |
Created at: April 30, 2026, 11:48 p.m.