Triple
T12917139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marilu Henner |
E309013
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Taxi |
E292660
|
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: [Marilu Henner, notableWork, Taxi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taxi Context triple: [Marilu Henner, notableWork, Taxi]
-
A.
Taxi
chosen
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.
Taksi
Taksi was a Jurchen chieftain of the late Ming period and the father of Nurhaci, whose lineage helped lay the foundations for the later Qing dynasty.
-
D.
Taksim
Taksim is a central district and major transportation and cultural hub on the European side of Istanbul, Turkey.
-
E.
Taxi for Two
Taxi for Two is a song by the pop group The Taxi Boys.
- 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_69d7bdf92b588190acdf2a2291ac4590 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971a1e8088190af697629baecf59f |
completed | April 10, 2026, 9:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a571a3e48190a32d362adc6eaee2 |
completed | May 3, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:41 p.m.