Triple
T11453492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Collège d'Orléans (tutored education) |
E271462
|
entity |
| Predicate | isTailored |
P83197
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Collège d'Orléans (tutored education), isTailored, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTailored Context triple: [Collège d'Orléans (tutored education), isTailored, true]
-
A.
hasContentTailoredTo
chosen
Indicates that something (such as a message, product, or experience) has its content specifically adapted or customized to suit a particular target, context, or audience.
-
B.
isSuitableFor
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with another entity.
-
C.
hasNotableTailor
Indicates that an entity is associated with a tailor who is distinguished or noteworthy in some significant way.
-
D.
customizableBy
Indicates that one entity can be modified, configured, or tailored in some way by another entity.
-
E.
isDesignedFor
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another entity.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d822f2138081909408c7916cef99c9 |
completed | April 9, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69d80867ff248190bb157fa9e355353b |
completed | April 9, 2026, 8:13 p.m. |
Created at: April 8, 2026, 9:35 p.m.