Triple
T38679002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Man in Chair |
E943835
|
entity |
| Predicate | timePeriodOfCharacter |
P119878
|
FINISHED |
| Object | contemporary to the musical’s production |
—
|
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: contemporary to the musical’s production | Statement: [Man in Chair, timePeriodOfCharacter, contemporary to the musical’s production]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timePeriodOfCharacter Context triple: [Man in Chair, timePeriodOfCharacter, contemporary to the musical’s production]
-
A.
followsLifeSpanOfCharacters
Indicates that one entity’s timeline or progression is structured to track or mirror the life spans of specified characters.
-
B.
characterInPeriod
chosen
Indicates that a character exists or is active during a specified historical or temporal period.
-
C.
tempoCharacter
Indicates the characteristic speed or pacing quality associated with an action, event, or process.
-
D.
screenTimeCharacter
Indicates the amount of time a particular character appears on screen within a given work or segment.
-
E.
timePeriodOfLife
Indicates the span or phase of time during which an entity exists, lives, or is active.
- 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_69f76eec28708190b9c82a505fc278e0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd91a5dad8819093eeeef527027890 |
completed | May 8, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69fd8f65fe9081908902500a3228d935 |
completed | May 8, 2026, 7:23 a.m. |
Created at: May 3, 2026, 4:33 p.m.