Triple
T37168717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Chidlom |
E920854
|
entity |
| Predicate | hasFashionSection |
P197376
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Central Chidlom, hasFashionSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFashionSection Context triple: [Central Chidlom, hasFashionSection, yes]
-
A.
hasClothingLine
Indicates that an entity owns, produces, or is associated with a specific line or brand of clothing.
-
B.
hasGarment
Indicates that one entity possesses, wears, or is associated with a particular garment.
-
C.
fashionCategory
Indicates the classification of an item into a specific fashion-related category or type (e.g., clothing, footwear, accessories).
-
D.
hasTeenSection
Indicates that an entity includes or provides a designated section or area specifically intended for teenagers.
-
E.
fashionFunction
Indicates a relationship where something serves a particular role, purpose, or use within the context of fashion (such as aesthetic, practical, cultural, or symbolic function).
- F. None of above. chosen
Provenance (4 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe8ddf70e48190a917eb9e8f7b6966 |
completed | May 9, 2026, 1:29 a.m. |
| PD | Predicate disambiguation | batch_69fe87ef94dc81909bb00ec8d6de9bcd |
completed | May 9, 2026, 1:03 a.m. |
| PDg | Predicate description generation | batch_69fe8dde8d008190b03dc0f97618073c |
completed | May 9, 2026, 1:29 a.m. |
Created at: May 3, 2026, 4:15 p.m.