Triple
T34180852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boissière metro station |
E876810
|
entity |
| Predicate | nearbySquareOrPlace |
P61270
|
FINISHED |
| Object | Place du Trocadéro et du 11 Novembre |
—
|
NE NERFINISHED |
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: Place du Trocadéro et du 11 Novembre | Statement: [Boissière metro station, nearbySquareOrPlace, Place du Trocadéro et du 11 Novembre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbySquareOrPlace Context triple: [Boissière metro station, nearbySquareOrPlace, Place du Trocadéro et du 11 Novembre]
-
A.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
-
B.
nearbyVenue
Indicates that one venue is located close to another venue in physical space.
-
C.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
D.
infrastructureNearby
Indicates that one entity is located close to another entity that serves as infrastructure (such as roads, utilities, or public facilities).
-
E.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current context.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fe68a4b67881909ca1d9f276f922e0 |
completed | May 8, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69fe680234c88190b01f953987b74972 |
completed | May 8, 2026, 10:47 p.m. |
Created at: May 1, 2026, 1:54 a.m.