Triple
T15297699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Deal |
E365700
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Nathan Larson |
E507928
|
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: Nathan Larson | Statement: [The Deal, composer, Nathan Larson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Larson Context triple: [The Deal, composer, Nathan Larson]
-
A.
Nathan Larson
chosen
Nathan Larson is an American musician and film composer known for scoring numerous independent and mainstream movies.
-
B.
Nathan Lind
Nathan Lind is a geologist and former Monarch scientist in the MonsterVerse franchise who helps orchestrate the expedition into the Hollow Earth in "Godzilla vs. Kong."
-
C.
Nathan Nugent
Nathan Nugent is a film editor known for his work on acclaimed independent and international films, including collaborations with director Sebastián Lelio.
-
D.
Nathan Johnson
Nathan Johnson is an American film composer and musician best known for his innovative, experimental scores for director Rian Johnson’s movies, including "Brick," "Looper," and "Knives Out."
-
E.
Nate Lahey
Nate Lahey is a former Philadelphia police detective and later private investigator who becomes deeply entangled in Annalise Keating’s criminal and personal turmoil in the TV series "How to Get Away with Murder."
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03686bfb8819080ba0caae652170a |
completed | April 16, 2026, 1:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21945b60819098ea91d9693cb8e3 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:15 a.m.