Triple
T34865622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Château de Latché |
E1004999
|
entity |
| Predicate | locatedInCountryEstateRegion |
P87581
|
FINISHED |
| Object | southwestern France |
—
|
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: southwestern France | Statement: [Château de Latché, locatedInCountryEstateRegion, southwestern France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInCountryEstateRegion Context triple: [Château de Latché, locatedInCountryEstateRegion, southwestern France]
-
A.
countryEstate
Indicates that a particular estate or property is located within or belongs to a specified country.
-
B.
landedEstatesRegion
chosen
Indicates that an entity’s landed estates are located within or associated with a particular geographic region.
-
C.
countryEstateType
Indicates the classification or category of an estate based on the country in which it is located or to which it belongs.
-
D.
countryEstateOf
Indicates that one entity is the rural or countryside property owned, controlled, or associated with another entity.
-
E.
countryHouseOnEstate
Indicates that a country house is located on, and forms part of, a particular estate.
- 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_69f76dbb678081909a247b9b5e1a73ac |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379ff1ba081908eda86acefcf69fb |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4 p.m.