Triple
T11526480
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place d’Italie station |
E273307
|
entity |
| Predicate | servesArrondissement |
P26130
|
FINISHED |
| Object | 13th arrondissement |
—
|
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: 13th arrondissement | Statement: [Place d’Italie station, servesArrondissement, 13th arrondissement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesArrondissement Context triple: [Place d’Italie station, servesArrondissement, 13th arrondissement]
-
A.
servesCommune
Indicates that an entity provides services or functions in support of a particular commune or local municipality.
-
B.
hasArrondissement
chosen
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
-
C.
officeStartTime (Mayor of 7th arrondissement)
Indicates the time at which the Mayor of the 7th arrondissement officially begins their term in office.
-
D.
servesPrefecture
Indicates that an entity (such as an organization, facility, or service) provides service or coverage to a specified prefecture.
-
E.
servesTownship
Indicates that an entity provides official services or administrative functions to a particular township.
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d87fd379648190b342e0c4b4f685b7 |
completed | April 10, 2026, 4:42 a.m. |
| PD | Predicate disambiguation | batch_69d80879fdb48190be6dacc8aa63c809 |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:37 p.m.