Triple
T14413464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speak (2004 film) |
E357387
|
entity |
| Predicate | hasTitleCharacterTrait |
P114157
|
FINISHED |
| Object | selective mutism |
—
|
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: selective mutism | Statement: [Speak (2004 film), hasTitleCharacterTrait, selective mutism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleCharacterTrait Context triple: [Speak (2004 film), hasTitleCharacterTrait, selective mutism]
-
A.
characterTitle
Indicates that a character holds or is associated with a specific title, rank, or formal designation.
-
B.
hasTitleCharacterRelation
Indicates a relationship where a title (such as a work or publication) is associated with or linked to a specific character appearing in it.
-
C.
hasMainTitleCharacter
Indicates that a work’s primary or main title is centered on, derived from, or explicitly names a particular character.
-
D.
hasSupportingCharacterTrait
Indicates that a supporting character possesses a particular trait, quality, or characteristic.
-
E.
titleCharacterString
Indicates that one entity is the textual string representing the title associated with another entity.
- F. None of above. chosen
Provenance (4 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90cb3c708190822f5506ebf7ee9d |
completed | April 14, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69de5c30467881908e770e3940295641 |
completed | April 14, 2026, 3:24 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:17 a.m.