Triple
T2306222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Versailles-Rive Droite station |
E51844
|
entity |
| Predicate | distanceFromParisSaintLazare |
P39082
|
FINISHED |
| Object | approximately 17 km |
—
|
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 17 km | Statement: [Versailles-Rive Droite station, distanceFromParisSaintLazare, approximately 17 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromParisSaintLazare Context triple: [Versailles-Rive Droite station, distanceFromParisSaintLazare, approximately 17 km]
-
A.
distanceFromParisCenter
Indicates the measured distance between a given location and the central point of Paris.
-
B.
distanceToFrance
Indicates the spatial distance between a given entity and the country of France.
-
C.
distanceToCharingCross
Indicates the spatial distance between a given location and Charing Cross.
-
D.
distanceToAmsterdamCentraal
Indicates the physical distance between a given location and Amsterdam Centraal station.
-
E.
distanceToGeneva
Indicates the spatial distance between a given entity and the location of Geneva.
- 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_69a88b0bb30c81908ded03b006d29387 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abce1f4f0c8190a714e4dcb8449f7e |
completed | March 7, 2026, 7:05 a.m. |
| PD | Predicate disambiguation | batch_69abc58ce2a081908ce2f0cadd92e9f8 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abce1e7c788190a15890feb2437f1d |
completed | March 7, 2026, 7:05 a.m. |
Created at: March 4, 2026, 7:49 p.m.