Triple
T2533232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 18th arrondissement of Paris |
E56209
|
entity |
| Predicate | arrondissementNumber |
P8975
|
FINISHED |
| Object | 18 |
—
|
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: 18 | Statement: [18th arrondissement of Paris, arrondissementNumber, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: arrondissementNumber Context triple: [18th arrondissement of Paris, arrondissementNumber, 18]
-
A.
hasArrondissement
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
-
B.
inseeCode
Indicates the official INSEE (French national statistics institute) code assigned to an entity, typically identifying a specific geographic or administrative unit.
-
C.
regionNumber
Indicates that an entity is assigned to or associated with a specific numbered region within a larger spatial or organizational division.
-
D.
communityDistrictNumber
Indicates the specific community district identifier associated with an entity or location.
-
E.
boroughNumber
chosen
Indicates the numerical identifier assigned to a specific borough within a larger administrative or municipal division.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd27afe7c8190984e10d3f3d5586b |
completed | March 7, 2026, 7:23 a.m. |
| PD | Predicate disambiguation | batch_69abd0c2e34c8190a914d5c2afba147c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:47 p.m.