Triple
T15553819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hailey Bieber |
E370817
|
entity |
| Predicate | hasModeledFor |
P17880
|
FINISHED |
| Object | Guess Accessories |
E219173
|
NE 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: Guess Accessories | Statement: [Hailey Bieber, hasModeledFor, Guess Accessories]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guess Accessories Context triple: [Hailey Bieber, hasModeledFor, Guess Accessories]
-
A.
Guess watches
Guess watches are fashion-forward timepieces from the American lifestyle brand Guess, known for their trendy designs and accessible pricing.
-
B.
Pockets
Pockets is a music producer known for contributing to Mos Def’s influential hip-hop album "Black on Both Sides."
-
C.
Guess
chosen
Guess is an American fashion brand known for its trendy denim, apparel, and accessories.
-
D.
Gant
Gant is a locality in the Swiss Alps situated close to the Findel Glacier, known as a starting point for alpine hiking and mountaineering routes.
-
E.
Gant
Gant is a surname most notably associated with American character actor Richard Gant, known for his roles in film and television since the 1980s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a96c0c88190808f68601a36b506 |
completed | April 16, 2026, 2:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456209288190aba6debd434af741 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:09 a.m.