Triple
T2765905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Josephine Butler College |
E61336
|
entity |
| Predicate | cateringModel |
P9631
|
FINISHED |
| Object | self-catered |
—
|
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: self-catered | Statement: [Josephine Butler College, cateringModel, self-catered]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cateringModel Context triple: [Josephine Butler College, cateringModel, self-catered]
-
A.
servesDish
Indicates that one entity prepares and presents a specific dish as food for another entity.
-
B.
servesVenue
Indicates that an entity provides services or functions in support of a particular venue.
-
C.
diningStyle
chosen
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
D.
servesEventType
Indicates that an entity provides or supports a particular type or category of event.
-
E.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
- F. None of above.
Provenance (3 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_69ab4b7bab6c8190a5c2efef19a8ef34 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfc5e1c8190a5ac2c48d3eaeb0a |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.