Triple
T14208771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salma Hayek |
E352169
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Salma |
E343693
|
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: Salma | Statement: [Salma Hayek, givenName, Salma]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salma Context triple: [Salma Hayek, givenName, Salma]
-
A.
Salma
chosen
Salma is a feminine given name of Arabic origin, commonly used in various cultures around the world.
-
B.
Najwa
Najwa is a Spanish actress and singer best known for her roles in series like "Money Heist" and her work in the electronic music duo Najwajean.
-
C.
Najma
Najma was the mother of Ali al-Rida, the eighth Shia Imam, and is venerated in Islamic tradition for her piety and role in his upbringing.
-
D.
Samira
Samira is a feminine given name of Arabic origin commonly used across the Middle East, North Africa, and South Asia.
-
E.
Shabana
Shabana is a prominent Bangladeshi film actress renowned for her extensive and influential career in Bengali cinema.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61fa8d24819092a8ec5d34c1c799 |
completed | April 14, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd19557f908190abb3dc116676f215 |
completed | May 7, 2026, 10:59 p.m. |
Created at: April 10, 2026, 1:05 a.m.