Triple
T29860197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Couvent des Célestins, Paris |
E758290
|
entity |
| Predicate | nearbyModernSite |
P33888
|
FINISHED |
| Object | Hôtel de Ville de Paris |
—
|
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: Hôtel de Ville de Paris | Statement: [Couvent des Célestins, Paris, nearbyModernSite, Hôtel de Ville de Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyModernSite Context triple: [Couvent des Célestins, Paris, nearbyModernSite, Hôtel de Ville de Paris]
-
A.
nearModernSite
chosen
Indicates that one entity is located in close physical proximity to a site or location from the modern era.
-
B.
notableNearbySite
Indicates that one entity is a significant or noteworthy site located close to another entity.
-
C.
nearbyRoyalSite
Indicates that one place or object is located close to a site associated with royalty, such as a palace, castle, or royal residence.
-
D.
nearbySitePartOf
Indicates that one site or site component is located close to and is considered part of another, larger site or site component.
-
E.
nearModernAvenue
Indicates that one entity is located close to or in the vicinity of a modern avenue.
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: April 29, 2026, 5:48 p.m.