Triple
T15104027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | María Isabel Verdú Rollán |
E360741
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Tetro |
E357350
|
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: Tetro | Statement: [María Isabel Verdú Rollán, notableWork, Tetro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tetro Context triple: [María Isabel Verdú Rollán, notableWork, Tetro]
-
A.
Tetro
chosen
Tetro is a 2009 drama film directed by Francis Ford Coppola, in which Maribel Verdú plays a key supporting role in a story about fractured family relationships and artistic rivalry in Buenos Aires.
-
B.
Tetritsqaro
Tetritsqaro is a town in southeastern Georgia that serves as a local administrative and transportation center within the Kvemo Kartli region.
-
C.
Tet
Tet is a river in the Pyrénées-Orientales department of southern France that flows from the Pyrenees to the Mediterranean Sea.
-
D.
Trife
Trife is a rapper best known as a member of the Brooklyn hip hop collective Junior M.A.F.I.A.
-
E.
Tikkana
Tikkana was a prominent 13th-century Telugu poet and scholar best known for translating a major portion of the Mahabharata into Telugu and helping shape classical Telugu literature.
- 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_69d85a0491ec8190830960be8fafb994 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00551521c8190b48d1a074bb4bdfc |
completed | April 15, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae274f6881908931569efc09996e |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3:05 a.m.