Triple
T30988366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barry Nelson as James Bond |
E789594
|
entity |
| Predicate | portrayalPrecedes |
P45032
|
FINISHED |
| Object | Sean Connery as James Bond |
—
|
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: Sean Connery as James Bond | Statement: [Barry Nelson as James Bond, portrayalPrecedes, Sean Connery as James Bond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayalPrecedes Context triple: [Barry Nelson as James Bond, portrayalPrecedes, Sean Connery as James Bond]
-
A.
portrayalStart
Indicates the point in time or sequence at which a particular portrayal or depiction of something begins.
-
B.
portrayalLedTo
Indicates that one entity’s portrayal of another caused or significantly contributed to a subsequent outcome, reaction, or state involving that other entity.
-
C.
successorPortrayal
chosen
Indicates that one portrayal of a character or role follows and replaces an earlier portrayal, typically by a different performer or in a later work.
-
D.
portrayalIntroduced
Indicates that one entity is introduced or presented as a portrayal or depiction of another entity.
-
E.
portrayalContinuity
Indicates that the same character is portrayed consistently across different works, installments, or versions, maintaining continuity in their depiction.
- F. None of above.
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_69f224c550b081909ddfceb0c3d03bdd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fdbc5ef46c8190bbcfb9798f4615b7 |
completed | May 8, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69fdbb270338819082ce3f73903e884f |
completed | May 8, 2026, 10:29 a.m. |
Created at: April 29, 2026, 8:56 p.m.