Triple
T325287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theme Building |
E6501
|
entity |
| Predicate | EncounterRestaurantOpening |
P12819
|
FINISHED |
| Object | 1997 |
—
|
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: 1997 | Statement: [Theme Building, EncounterRestaurantOpening, 1997]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: EncounterRestaurantOpening Context triple: [Theme Building, EncounterRestaurantOpening, 1997]
-
A.
restaurantName
Indicates the name assigned to a restaurant as its identifying label.
-
B.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
C.
reopeningDate
Indicates the date on which something that was previously closed is opened again for use or access.
-
D.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
E.
venueConcept
Indicates a relationship where a venue is associated with, characterized by, or defined in terms of a particular concept or thematic idea.
- 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_69a2e7933d6c8190bb2592ad13286ef2 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1a37c08190b1380f6bf8513a37 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e949364c8190bc2351f5413f5057 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2eb18bda48190ac3d96a61a6a684d |
completed | Feb. 28, 2026, 1:18 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.