Triple
T10920456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maya Lopez |
E257932
|
entity |
| Predicate | creators |
P7732
|
FINISHED |
| Object | David Mack |
E632069
|
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: David Mack | Statement: [Maya Lopez, creators, David Mack]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Mack Context triple: [Maya Lopez, creators, David Mack]
-
A.
David Mack
chosen
David Mack is an American author best known for his numerous Star Trek tie-in novels and related science fiction works.
-
B.
Alan Ford
Alan Ford is a British character actor best known for his tough-guy and gangster roles in films by director Guy Ritchie.
-
C.
Nick Meyer
Nick Meyer is a film executive and producer known for his work on major studio projects, including the fantasy adventure film "Dungeons & Dragons: Honor Among Thieves."
-
D.
Paul Darrow
Paul Darrow was the son of famed American lawyer Clarence Darrow and a businessman who managed many of his father's financial affairs.
-
E.
Brian MacDevitt
Brian MacDevitt is a Tony Award–winning American lighting designer renowned for his work on numerous high-profile Broadway productions.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77081a0c48190b7aa4a482032d1ea |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2171adbbc8190916a5463b6e5c186 |
completed | April 17, 2026, 11:18 a.m. |
Created at: April 8, 2026, 9:22 p.m.