Triple
T28987873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Breteuil |
E734737
|
entity |
| Predicate | distanceToBeauvaisKilometres |
P202152
|
FINISHED |
| Object | about 30 |
—
|
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 30 | Statement: [Breteuil, distanceToBeauvaisKilometres, about 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBeauvaisKilometres Context triple: [Breteuil, distanceToBeauvaisKilometres, about 30]
-
A.
distanceFromBesançonKilometres
Indicates the distance, measured in kilometers, between an entity and the city of Besançon.
-
B.
distanceToGatineauByRoad_km
Indicates the length, in kilometers, of the road route needed to travel from an entity to Gatineau.
-
C.
distanceFromFoixKilometres
Indicates the physical distance, measured in kilometers, between a given place or entity and the location of Foix.
-
D.
distanceToMeauxKilometersApprox
Indicates the approximate distance, measured in kilometers, between a given location and Meaux.
-
E.
distanceFromQuebecCity
Indicates the measured distance between a given place or object and Quebec City.
- 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_69f05b0dd9b481908b7901e1c95ff6b2 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a005b2e0a9c819081c6f7ccbef49ff8 |
completed | May 10, 2026, 10:17 a.m. |
| PD | Predicate disambiguation | batch_6a005a8bcde88190ace2bc0215e26430 |
completed | May 10, 2026, 10:14 a.m. |
| PDg | Predicate description generation | batch_6a005b2cdbc881908b433623e3252df5 |
completed | May 10, 2026, 10:17 a.m. |
Created at: April 28, 2026, 9:15 a.m.