Triple
T22759854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saray Vargas de Jesús |
E562954
|
entity |
| Predicate | hasRelationshipWith |
P2830
|
FINISHED |
| Object | Zulema Zahir |
—
|
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: Zulema Zahir | Statement: [Saray Vargas de Jesús, hasRelationshipWith, Zulema Zahir]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zulema Zahir Context triple: [Saray Vargas de Jesús, hasRelationshipWith, Zulema Zahir]
-
A.
Zulema Zahir
chosen
Zulema Zahir is a ruthless and cunning inmate who becomes one of the central antagonists in the Spanish prison drama series "Vis a Vis" ("Locked Up").
-
B.
Zara Kaleel
Zara Kaleel is the central character in Kia Abdullah’s legal thriller series, a British-Muslim barrister known for her fierce pursuit of justice in complex, emotionally charged court cases.
-
C.
Zana Khan
Zana Khan is a town in Ghazni Province, Afghanistan, serving as the administrative center of Zana Khan District.
-
D.
Zainab Azizi
Zainab Azizi is a film producer known for her work on the 2023 movie "65."
-
E.
Tammea Ziya
Tammea Ziya is known as the spouse of Canadian actor Adam Beach.
- 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_69e24552e11c81909c2d61578a558bd7 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17a7b4fe88190b1da25b78f046d13 |
completed | April 29, 2026, 3:26 a.m. |
Created at: April 17, 2026, 3:26 p.m.