Triple
T29092497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madame Mallory |
E734891
|
entity |
| Predicate | restaurantStatus |
P166304
|
FINISHED |
| Object | Michelin-starred restaurant |
—
|
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: Michelin-starred restaurant | Statement: [Madame Mallory, restaurantStatus, Michelin-starred restaurant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restaurantStatus Context triple: [Madame Mallory, restaurantStatus, Michelin-starred restaurant]
-
A.
restaurantContained
Indicates that a restaurant is physically located within or is a part of a larger place or establishment.
-
B.
restaurantName
Indicates the name assigned to a restaurant as its identifying label.
-
C.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
D.
openedAsRestaurant
Indicates that an entity began operating or was first established in the capacity or function of a restaurant.
-
E.
restaurantOperator
Indicates that one entity operates, manages, or runs a restaurant business 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_69f05b0ed66481908f2e864fa550d2f1 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6617e62fc8190b9a935835fc82bfa |
completed | May 2, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69f65c2376a08190be5215171e908e69 |
completed | May 2, 2026, 8:18 p.m. |
| PDg | Predicate description generation | batch_69f65f75ac608190a62cd6afce14f68e |
completed | May 2, 2026, 8:32 p.m. |
Created at: April 28, 2026, 11:06 a.m.