Triple
T29673696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Disney Casual Table-Service Dining category |
E750742
|
entity |
| Predicate | oftenOffers |
P180879
|
FINISHED |
| Object | themed decor |
—
|
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: themed decor | Statement: [Disney Casual Table-Service Dining category, oftenOffers, themed decor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenOffers Context triple: [Disney Casual Table-Service Dining category, oftenOffers, themed decor]
-
A.
offersMass
Indicates that one entity provides or makes available a certain mass or quantity of material or substance to another entity.
-
B.
offersMarket
Indicates that one entity provides or makes available a market (as a venue or opportunity for buying, selling, or trading) to another entity.
-
C.
offersDealTo
Indicates that one entity proposes or presents a deal, offer, or agreement to another entity.
-
D.
offersObject
Indicates that a subject provides or makes available a specific object to another party as an offer.
-
E.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
- 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_69f0d624d7b08190ba237d226f78d0d9 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
| PDg | Predicate description generation | batch_69f75788d40c819083bf2567b3091585 |
completed | May 3, 2026, 2:11 p.m. |
Created at: April 28, 2026, 7:06 p.m.