Triple
T7071913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Cagney |
E164718
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Taxi! |
E55553
|
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: Taxi! | Statement: [James Cagney, notableWork, Taxi!]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taxi! Context triple: [James Cagney, notableWork, Taxi!]
-
A.
Taxi
Taxi is a critically acclaimed American sitcom that aired from 1978 to 1983, following the lives of New York City cab drivers and their dispatcher, and is celebrated for its ensemble cast and blend of comedy and pathos.
-
B.
Taxi
Taxi is a 2015 Iranian docu-fiction film directed by Jafar Panahi, set almost entirely inside a Tehran taxi as it explores everyday life and social issues in contemporary Iran.
-
C.
Taxi 2
Taxi 2 is a 2000 French action-comedy film and sequel in the Taxi franchise, known for its high-speed car chases and humorous storyline set in Marseille.
-
D.
Taxi (2004 film)
chosen
Taxi (2004 film) is an American action-comedy movie about a speedy New York City cab driver who teams up with a bumbling cop to catch a gang of bank robbers.
-
E.
Dubai Taxi
Dubai Taxi is a government-regulated taxi service in Dubai that provides metered transportation across the city and complements the public transit network.
- 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_69c6887b96548190a8a9b3ac8adf4119 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e4c9cdbc8190b91cd3b4eef58eb6 |
completed | March 27, 2026, 8:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7945fdafc81909c265373627af4e8 |
completed | March 28, 2026, 8:42 a.m. |
Created at: March 27, 2026, 2:39 p.m.