Triple
T14274899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Queen Victoria pub |
E353889
|
entity |
| Predicate | hasFictionalRoomType |
P71478
|
FINISHED |
| Object | public bar |
—
|
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: public bar | Statement: [The Queen Victoria pub, hasFictionalRoomType, public bar]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalRoomType Context triple: [The Queen Victoria pub, hasFictionalRoomType, public bar]
-
A.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
-
B.
hasFictionalEstablishmentType
chosen
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
C.
hasPeriodRooms
Indicates that an entity contains rooms that are decorated or preserved to reflect specific historical periods.
-
D.
hasStateRooms
Indicates that an entity (such as a ship, building, or facility) contains or is equipped with state rooms.
-
E.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6582f5308190969f4cfd724d9139 |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.