Triple
T21705206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pol Antràs |
E535755
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Antràs |
—
|
NE NERFINISHED |
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: Antràs | Statement: [Pol Antràs, familyName, Antràs]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antràs Context triple: [Pol Antràs, familyName, Antràs]
-
A.
Antràs
chosen
Antràs is the surname of Pol Antràs, a prominent Spanish economist known for his work in international trade and globalization.
-
B.
Mansueto
Mansueto is an Italian-origin surname most notably associated with billionaire entrepreneur and Morningstar founder Joe Mansueto.
-
C.
Malaueg
Malaueg is an Austronesian language spoken by the Malaueg people in the northern Philippines, particularly in the province of Cagayan.
-
D.
Olitski
Olitski is the surname of Jules Olitski, a prominent Russian-American abstract painter associated with Color Field painting and the Washington Color School.
-
E.
Prochiantz
Prochiantz is the surname of Alain Prochiantz, a prominent French neuroscientist known for his work on brain development and homeoprotein signaling.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c46b44c0819088ab883ebd44e0e8 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69efb52e4b84819095a24cc9fdca2b8a |
completed | April 27, 2026, 7:12 p.m. |
Created at: April 16, 2026, 6:46 p.m.