Triple
T33157361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Châtre |
E848617
|
entity |
| Predicate | nearbyLiterarySite |
P19575
|
FINISHED |
| Object | Maison de George Sand in Nohant-Vic |
—
|
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: Maison de George Sand in Nohant-Vic | Statement: [La Châtre, nearbyLiterarySite, Maison de George Sand in Nohant-Vic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyLiterarySite Context triple: [La Châtre, nearbyLiterarySite, Maison de George Sand in Nohant-Vic]
-
A.
nearbyHeritageDestinations
Indicates that one or more heritage destinations are located close to a given reference point or entity in geographic space.
-
B.
notableNearbySite
chosen
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.
locatedNearFiction
Indicates that one fictional entity or place is situated close to another within an imagined or narrative context.
-
E.
nearbyWorldHeritageSite
Indicates that one entity is located close to, or in the immediate vicinity of, a designated World Heritage Site.
- 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_69f3495b02d08190bb3d366823dffc21 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fdee770af48190aca2670db50f8b49 |
completed | May 8, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69fdecec98a08190a357d816dc2a6dbe |
completed | May 8, 2026, 2:02 p.m. |
Created at: May 1, 2026, 1:28 a.m.