Triple
T4366849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fore Street (Portland, Maine) |
E98795
|
entity |
| Predicate | hasDiningFeature |
P55802
|
FINISHED |
| Object | open kitchen |
—
|
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: open kitchen | Statement: [Fore Street (Portland, Maine), hasDiningFeature, open kitchen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiningFeature Context triple: [Fore Street (Portland, Maine), hasDiningFeature, open kitchen]
-
A.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
B.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
C.
diningStyle
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
D.
hasRevolvingRestaurant
Indicates that one entity features or contains a restaurant that rotates around a central axis, typically providing a 360-degree view.
-
E.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
- 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_69b3454db3708190aeafd814413c4c3d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35201be7081908808e81634060f95 |
completed | March 12, 2026, 11:53 p.m. |
| PD | Predicate disambiguation | batch_69b34f53e3cc8190bf5d4dbe2413bf65 |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff654308190b9717526120d80d3 |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:17 p.m.