Triple
T34031610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gladys Green |
E872667
|
entity |
| Predicate | galleryThreat |
P43422
|
FINISHED |
| Object | closure of her Waverly Place gallery |
—
|
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: closure of her Waverly Place gallery | Statement: [Gladys Green, galleryThreat, closure of her Waverly Place gallery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: galleryThreat Context triple: [Gladys Green, galleryThreat, closure of her Waverly Place gallery]
-
A.
facesThreat
chosen
Indicates that an entity is exposed to or confronted by a potential danger, risk, or harmful situation.
-
B.
hasThreats
Indicates that one entity poses or is associated with potential danger, harm, or adverse consequences toward another entity.
-
C.
featuresThreat
Indicates that one entity includes, presents, or contains a threat associated with another entity.
-
D.
laterThreat
Indicates that one entity poses a threat to another at a time subsequent to some referenced or initial point.
-
E.
recognizesThreat
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
- 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_69f349a2527c81909a7cd4bda94d70ad |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70b966860819089cf92927f47c5f1 |
completed | May 3, 2026, 8:47 a.m. |
| PD | Predicate disambiguation | batch_69f70abe43e08190b2a30930d96247c1 |
completed | May 3, 2026, 8:43 a.m. |
Created at: May 1, 2026, 1:51 a.m.