Triple
T22020894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mojo |
E543842
|
entity |
| Predicate | hasAdaptation |
P1690
|
FINISHED |
| Object | Mojo (1997 film) |
—
|
NE NERFINISHED |
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: Mojo (1997 film) | Statement: [Mojo, hasAdaptation, Mojo (1997 film)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mojo (1997 film) Context triple: [Mojo, hasAdaptation, Mojo (1997 film)]
-
A.
Mojo (1997 film)
chosen
Mojo is a 1997 British black comedy crime film, adapted from Jez Butterworth’s stage play, set in London’s Soho nightclub scene of the late 1950s.
-
B.
Mojo
Mojo is a town in central Ethiopia located along major transport routes southeast of Addis Ababa.
-
C.
Mojo
Mojo is a 2010 blues-rock–oriented studio album by Tom Petty and the Heartbreakers that marked their return to a raw, live-in-the-studio sound.
-
D.
Mojo
Mojo is a high-performance programming language designed by Modular Inc. to combine Python’s usability with systems-level speed and capabilities for AI and compute-intensive workloads.
-
E.
Mojo
Mojo is a darkly comic stage play by British playwright Jez Butterworth, set in 1950s Soho and centered on the seedy underworld of a London nightclub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127c7b3308190ac056bef6f82722e |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:23 p.m.