Triple
T23271606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Restaurant Gordon Ramsay |
E588304
|
entity |
| Predicate | offersWinePairing |
P151626
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Restaurant Gordon Ramsay, offersWinePairing, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersWinePairing Context triple: [Restaurant Gordon Ramsay, offersWinePairing, yes]
-
A.
winePairing
Indicates a relationship where a particular wine is recommended as a suitable accompaniment for a given food or dish.
-
B.
wineServingSuggestion
Indicates the recommended way or context in which a particular wine is best served or enjoyed.
-
C.
sweetWineSuitability
Indicates the degree to which something is appropriate or recommended for pairing with or serving as a sweet wine.
-
D.
offersMeal
Indicates that one entity provides or makes available a meal to another entity.
-
E.
typicalFoodPairing
Indicates that one food item is commonly served, consumed, or matched together with another as a customary or complementary pairing.
- 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_69e25d148adc819088efbf42672604e9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1957418fc819085ee528622e0c6de |
completed | April 29, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:46 p.m.