Triple
T29748433
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stade de la Vallée du Cher |
E752823
|
entity |
| Predicate | hasLocationDepartment |
P153033
|
FINISHED |
| Object | Indre-et-Loire |
—
|
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: Indre-et-Loire | Statement: [Stade de la Vallée du Cher, hasLocationDepartment, Indre-et-Loire]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocationDepartment Context triple: [Stade de la Vallée du Cher, hasLocationDepartment, Indre-et-Loire]
-
A.
basedInDepartment
Indicates that an entity operates or has its primary affiliation within a specific department.
-
B.
hasLocationRole
Indicates that an entity holds or plays a specific role in relation to a particular location (e.g., origin, destination, storage site, or operational area).
-
C.
hasDistrictOfficeLocation
Indicates that an entity’s district office is located at a specified place or address.
-
D.
locatedInModernDepartment
chosen
Indicates that an entity is geographically situated within the boundaries of a present-day administrative department.
-
E.
hasDepartmentSeatRole
Indicates that an entity holds a specific role or position associated with a seat in a particular department.
- 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_69f0d62c84cc8190846f80ae04fdf8ec |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
Created at: April 28, 2026, 7:52 p.m.