Triple
T35181172
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detective Temple Page |
E1015851
|
entity |
| Predicate | playedByCharacterAgeRange |
P98619
|
FINISHED |
| Object | adult |
—
|
LITERAL 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: adult | Statement: [Detective Temple Page, playedByCharacterAgeRange, adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playedByCharacterAgeRange Context triple: [Detective Temple Page, playedByCharacterAgeRange, adult]
-
A.
portrayedByCharacterAgeApprox
chosen
Indicates that an entity is portrayed by a character whose age is approximately a specified value or age range.
-
B.
playedBy
Indicates that a role, character, or performance is portrayed or executed by a specific person or agent.
-
C.
oftenPlayedBy
Indicates that one entity frequently performs, portrays, or executes another entity, such as a role, character, or piece of music.
-
D.
arePlayedBy
Indicates that one or more performers (such as actors or musicians) carry out, interpret, or execute the referenced roles, characters, or pieces.
-
E.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
- 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_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: May 3, 2026, 4:02 p.m.