Triple
T1296411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umrah |
E27661
|
entity |
| Predicate | pilgrimsTypicallyWear |
P271
|
FINISHED |
| Object | two white seamless cloths for men |
—
|
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: two white seamless cloths for men | Statement: [Umrah, pilgrimsTypicallyWear, two white seamless cloths for men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pilgrimsTypicallyWear Context triple: [Umrah, pilgrimsTypicallyWear, two white seamless cloths for men]
-
A.
nationalDress
Indicates that an item of clothing is recognized as the traditional or customary dress associated with a particular nation or culture.
-
B.
wears
chosen
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.
wornAs
Indicates that one entity is used or put on as clothing, an accessory, or a wearable item by another entity.
-
E.
pilgrimageAssociatedWith
Indicates a relationship where a pilgrimage is connected or related to a particular entity, such as a place, person, event, or religious tradition.
- 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_69a496d6682881909ba658f1c1e0e2b0 |
completed | March 1, 2026, 7:43 p.m. |
| NER | Named-entity recognition | batch_69a4c3bb3a9c81909db2ad91defd87b6 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bee64d908190b6a9bb479959d523 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:51 p.m.