Triple
T8994113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zorba the Greek |
E214858
|
entity |
| Predicate | portrays |
P264
|
FINISHED |
| Object | Alan Bates as Basil |
E190481
|
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: Alan Bates as Basil | Statement: [Zorba the Greek, portrays, Alan Bates as Basil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alan Bates as Basil Context triple: [Zorba the Greek, portrays, Alan Bates as Basil]
-
A.
Alan Bates
chosen
Alan Bates was an acclaimed English actor known for his intense, nuanced performances in film, television, and theatre from the 1960s onward.
-
B.
Anthony Perkins
Anthony Perkins was an American actor best known for his iconic role as Norman Bates in Alfred Hitchcock’s film "Psycho."
-
C.
Marcel Lindon
Marcel Lindon is the son of French actor Vincent Lindon.
-
D.
Bill Bates
Bill Bates is a former American football safety best known for his long and successful career with the Dallas Cowboys in the NFL.
-
E.
Alan Baxter
Alan Baxter was an American character actor known for his roles in mid-20th-century film and television, often portraying tough or villainous figures.
- 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc687798a881908e6fdd9a39219f1d |
completed | April 1, 2026, 12:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfd0cd2b948190947a26fe11ad81bf |
completed | April 3, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:04 p.m.