Triple
T518587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyatt Regency Dallas |
E10762
|
entity |
| Predicate | numberOfRestaurants |
P15337
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Hyatt Regency Dallas, numberOfRestaurants, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfRestaurants Context triple: [Hyatt Regency Dallas, numberOfRestaurants, multiple]
-
A.
numberOfVenues
Indicates the total count of venues associated with a given entity or context.
-
B.
restaurantName
Indicates the name assigned to a restaurant as its identifying label.
-
C.
numberOfStores
Indicates the total count of stores associated with a given entity or context.
-
D.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
E.
EncounterRestaurantOpening
Indicates a situation where an entity comes across or experiences the opening or start of operations of a restaurant.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f19ee6748190916603ef3a9e27f3 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f0151e8c81909a82b58ac0515eba |
completed | Feb. 28, 2026, 1:39 p.m. |
| PDg | Predicate description generation | batch_69a2f1137e948190838303cdaa757a5a |
completed | Feb. 28, 2026, 1:43 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.