Triple
T2899255
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jon Kortajarena |
E62615
|
entity |
| Predicate | hasWorkedAsFaceOfBrand |
P29719
|
FINISHED |
| Object | Zara |
E137996
|
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: Zara | Statement: [Jon Kortajarena, hasWorkedAsFaceOfBrand, Zara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zara Context triple: [Jon Kortajarena, hasWorkedAsFaceOfBrand, Zara]
-
A.
Zara
chosen
Zara is the historical Italian name for the coastal Croatian city of Zadar on the Adriatic Sea.
-
B.
H&M
H&M is a global fast-fashion retail chain known for offering trendy clothing and accessories at affordable prices.
-
C.
Uniqlo
Uniqlo is a global Japanese clothing retailer known for its affordable, minimalist casual wear and functional basics.
-
D.
Primark
Primark is a major Irish-founded fast-fashion retail chain known for its low-priced clothing, accessories, and home goods, operating under the Penneys brand in Ireland and Primark elsewhere in Europe and the United States.
-
E.
Semler
Semler is a German surname most notably associated with Johann Salomo Semler, an influential 18th-century biblical scholar and theologian.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0ad7bbc8190822738baa6935b74 |
completed | March 7, 2026, 8:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b055fe13448190bf25832219fd5f0c |
completed | March 10, 2026, 5:33 p.m. |
Created at: March 6, 2026, 10:10 p.m.