Triple
T6788674
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justice for All with Judge Cristina Perez |
E155876
|
entity |
| Predicate | hasOpeningMonologue |
P9712
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Justice for All with Judge Cristina Perez, hasOpeningMonologue, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningMonologue Context triple: [Justice for All with Judge Cristina Perez, hasOpeningMonologue, true]
-
A.
includesSpokenPrologue
chosen
Indicates that an entity (such as a work or performance) contains a spoken introductory section delivered before the main content begins.
-
B.
spokenBefore
Indicates that one entity has spoken or produced speech earlier in time than another entity.
-
C.
hasProseDialogue
Indicates that one entity contains or features spoken or conversational content expressed in prose form involving another entity.
-
D.
hasOpening
Indicates that one entity possesses or features an opening, gap, or entrance that allows access, passage, or exposure.
-
E.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
- 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_69c6881770fc8190972b2906390380f5 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2aa2e0c8190b994261826ae001d |
completed | March 27, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69c6d0979ce0819094678896da4e3169 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:14 p.m.