Triple
T38526090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clos Montmartre |
E923231
|
entity |
| Predicate | landmarkNearby |
P19575
|
FINISHED |
| Object | Basilique du Sacré-Cœur |
—
|
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: Basilique du Sacré-Cœur | Statement: [Clos Montmartre, landmarkNearby, Basilique du Sacré-Cœur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landmarkNearby Context triple: [Clos Montmartre, landmarkNearby, Basilique du Sacré-Cœur]
-
A.
typicalNearbyLandmarks
Indicates that certain landmarks are commonly found in the vicinity of a given place or location.
-
B.
nearbyHeritageDestinations
Indicates that one or more heritage destinations are located close to a given reference point or entity in geographic space.
-
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.
notableNearbySite
chosen
Indicates that one entity is a significant or noteworthy site located close to another entity.
-
E.
infrastructureNearby
Indicates that one entity is located close to another entity that serves as infrastructure (such as roads, utilities, or public facilities).
- 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_69f76ea8f6348190a5c03fb6292bbee3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd313e61c8190b174b331365b803f |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:32 p.m.