Triple
T5884860
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adil Hussain |
E130836
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Adil Hussain |
E130836
|
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: Adil Hussain | Statement: [Adil Hussain, name, Adil Hussain]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adil Hussain Context triple: [Adil Hussain, name, Adil Hussain]
-
A.
Adil Hussain
chosen
Adil Hussain is an Indian actor known for his nuanced performances in both Indian and international films, as well as in theatre and television.
-
B.
Abdul Mateen
Abdul Mateen is a Bruneian prince and public figure known for his military career, international diplomacy, and prominent presence in regional and global events.
-
C.
Nadim Sawalha
Nadim Sawalha is a Jordanian-British actor known for his character roles in film and television, including appearances in James Bond movies and various British dramas.
-
D.
Riz Ahmed
Riz Ahmed is a British actor and rapper acclaimed for his roles in films like "Nightcrawler," "Rogue One," and the Oscar-winning "The Long Goodbye."
-
E.
Stephen Dillane
Stephen Dillane is a British actor known for his nuanced performances in film, television, and theatre, including roles in "Game of Thrones," "The Tunnel," and "The Hours."
- 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_69c0085628dc8190b334c1b44c067efc |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0367743508190bae211e9ce8f9690 |
completed | March 22, 2026, 6:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b13839f48190b23f22d5317eb571 |
completed | March 23, 2026, 3:19 a.m. |
Created at: March 22, 2026, 3:57 p.m.