Triple
T9991092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Récollets |
E196886
|
entity |
| Predicate | woreHabit |
P84687
|
FINISHED |
| Object | brown Franciscan habit |
—
|
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: brown Franciscan habit | Statement: [Récollets, woreHabit, brown Franciscan habit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: woreHabit Context triple: [Récollets, woreHabit, brown Franciscan habit]
-
A.
wornAs
Indicates that one entity is used or put on as clothing, an accessory, or a wearable item by another entity.
-
B.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
C.
wornOver
Indicates that one item of clothing or accessory is positioned on top of and covering another item when worn.
-
D.
wornAt
Indicates that an item is being worn on a specific part of the body or at a particular time or event.
-
E.
typicallyWornBy
chosen
Indicates that something (such as an item or garment) is most commonly or characteristically worn by a particular type of person or group.
- 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_69ca82f1678c819093d06320a05f16a4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdc7a0cb6481908d7bd1b43f93bd18 |
completed | April 2, 2026, 1:34 a.m. |
| PD | Predicate disambiguation | batch_69cd1da07db88190945bcdab3ca82e71 |
completed | April 1, 2026, 1:29 p.m. |
Created at: March 30, 2026, 8:50 p.m.