Triple
T29435298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben Affleck as George Reeves |
E746553
|
entity |
| Predicate | relatedRealPerson |
P86334
|
FINISHED |
| Object | George Reeves |
—
|
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: George Reeves | Statement: [Ben Affleck as George Reeves, relatedRealPerson, George Reeves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedRealPerson Context triple: [Ben Affleck as George Reeves, relatedRealPerson, George Reeves]
-
A.
characterRealWorldCounterpart
chosen
Indicates that a fictional character is based on, inspired by, or directly corresponds to a specific real-world person.
-
B.
realPersonAffiliation
Indicates a relationship where a real person is formally associated or connected with an organization, group, or entity.
-
C.
relationshipTarget
Indicates that an entity is the object or recipient toward which a specified relationship is directed.
-
D.
realPerson
Indicates that the referenced entity corresponds to an actual human individual, as opposed to a fictional, anonymous, or non-human entity.
-
E.
realPersonDepicted
Indicates that a real, actual person (not fictional or generic) is visually represented or shown in the subject entity.
- 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_69f0a7a180e48190ae775e40047dbcb5 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a01378bf05c8190af9f5e06a2810c7d |
completed | May 11, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_6a0137277c6c8190bcec341f2a0757c4 |
completed | May 11, 2026, 1:55 a.m. |
Created at: April 28, 2026, 3:16 p.m.