Triple
T19724814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pier A Harbor House |
E473697
|
entity |
| Predicate | openedAsRestaurant |
P137087
|
FINISHED |
| Object | 2014 |
—
|
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: 2014 | Statement: [Pier A Harbor House, openedAsRestaurant, 2014]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openedAsRestaurant Context triple: [Pier A Harbor House, openedAsRestaurant, 2014]
-
A.
EncounterRestaurantOpening
Indicates a situation where an entity comes across or experiences the opening or start of operations of a restaurant.
-
B.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
C.
homeVenueOpened
Indicates that a venue has officially begun operating as the designated home location for a particular team or organization.
-
D.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
E.
EncounterRestaurantClosure
Indicates that an entity experiences or comes across the situation of a restaurant being closed.
- 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_69d8e517ebd48190979ee76723bcfadf |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e649f70bac8190823cb3dfbd085a99 |
completed | April 20, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
| PDg | Predicate description generation | batch_69e532bbedf081908d801600e2af94a7 |
completed | April 19, 2026, 7:53 p.m. |
Created at: April 10, 2026, 1:46 p.m.