Triple
T22268686
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gap Inc. |
E550416
|
entity |
| Predicate | hasKeyMarketSegment |
P120776
|
FINISHED |
| Object | family apparel |
—
|
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: family apparel | Statement: [Gap Inc., hasKeyMarketSegment, family apparel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasKeyMarketSegment Context triple: [Gap Inc., hasKeyMarketSegment, family apparel]
-
A.
hasMarketSegmentFor
chosen
Indicates that an entity targets or serves a specific market segment for its products or services.
-
B.
hasUserSegment
Indicates that an entity is associated with a particular user segment or group of users defined by shared characteristics or behaviors.
-
C.
hasMarketSector
Indicates that an entity operates within, is associated with, or belongs to a particular market sector or industry segment.
-
D.
marketSegmentType
Indicates the specific category or segment of the market that an entity, product, or service is targeted toward or associated with.
-
E.
hasMarketingCategory
Indicates that an entity is associated with a specific marketing category or segment used for classification or targeting.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141bde9f88190b533bcb88787b492 |
completed | April 28, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69e72ff0363081909f794d19c8a64837 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:39 p.m.