Triple
T33659614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Open All Hours |
E862314
|
entity |
| Predicate | hasOpeningDevice |
P187407
|
FINISHED |
| Object | dangerous shop till |
—
|
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: dangerous shop till | Statement: [Open All Hours, hasOpeningDevice, dangerous shop till]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOpeningDevice Context triple: [Open All Hours, hasOpeningDevice, dangerous shop till]
-
A.
hasOpening
Indicates that one entity possesses or features an opening, gap, or entrance that allows access, passage, or exposure.
-
B.
hasOpeningSetting
Indicates that one entity (typically a narrative work) has its initial scene or setting located in the other entity.
-
C.
hasOpeningType
Indicates that one entity has, features, or is characterized by a particular type or kind of opening.
-
D.
hasOpeningFeature
Indicates that an entity possesses a specific characteristic, element, or attribute related to its opening or entry point.
-
E.
hasOpenedFor
Indicates that one entity has performed or appeared as the opening act or preliminary participant for another entity, typically in an event or performance context.
- 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_69f34984c4008190bb82f33a7819da64 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69fb563a28d88190b28345c465c545f8 |
completed | May 6, 2026, 2:54 p.m. |
Created at: May 1, 2026, 1:42 a.m.