Triple
T14980945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grenelle |
E373571
|
entity |
| Predicate | quartierNumber |
P92850
|
FINISHED |
| Object | 57 |
—
|
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: 57 | Statement: [Grenelle, quartierNumber, 57]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quartierNumber Context triple: [Grenelle, quartierNumber, 57]
-
A.
situatedInQuarter
Indicates that one entity is located within or belongs to a specific quarter or district of a larger area.
-
B.
cityQuarterNumber
chosen
Indicates the specific numbered quarter or district within a city to which an entity belongs or is associated.
-
C.
boroughNumber
Indicates the numerical identifier assigned to a specific borough within a larger administrative or municipal division.
-
D.
communityDistrictNumber
Indicates the specific community district identifier associated with an entity or location.
-
E.
hasArrondissement
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
- 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_69d85ccbbcd48190acb56e7cf104d8ad |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6fcebf481909f72cab577560d82 |
completed | April 15, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69de9a6169b48190a679609febd2d0e3 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:52 a.m.