Triple
T8771912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Necker district |
E208483
|
entity |
| Predicate | locatedInCitySubdivision |
P74415
|
FINISHED |
| Object | southwestern Paris |
—
|
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: southwestern Paris | Statement: [Necker district, locatedInCitySubdivision, southwestern Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCitySubdivision Context triple: [Necker district, locatedInCitySubdivision, southwestern Paris]
-
A.
citySubdivision
chosen
Indicates that one administrative or geographic unit is a smaller subdivision contained within a larger city.
-
B.
locatedInRegionalDistrict
Indicates that one entity is geographically situated within the boundaries of a specified regional district.
-
C.
locatedInCityWard
Indicates that one entity is situated within the administrative boundaries of a specific city ward.
-
D.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
E.
partOfCountrySubdivision
Indicates that one geographic or administrative unit is contained within and forms a component part of a larger country subdivision.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2c54c08190a904723d1f0527a4 |
completed | March 31, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:41 p.m.