Triple
T22779774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Stephen’s House, Oxford |
E563800
|
entity |
| Predicate | typeOfHall |
P149695
|
FINISHED |
| Object | permanent private hall |
—
|
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: permanent private hall | Statement: [St Stephen’s House, Oxford, typeOfHall, permanent private hall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfHall Context triple: [St Stephen’s House, Oxford, typeOfHall, permanent private hall]
-
A.
auditoriumType
Indicates the specific kind or category of auditorium associated with an entity.
-
B.
typeOfChamber
Indicates the specific kind or category of chamber that an entity belongs to or is classified as.
-
C.
hasSingleHall
Indicates that an entity possesses exactly one hall within its structure or domain.
-
D.
hasMainHallType
Indicates the specific category or kind of main hall associated with an entity.
-
E.
chamberType
Indicates the specific kind or category of chamber associated with an entity (e.g., room, compartment, or enclosed space type).
- 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_69e24554497c819080b996e071de27c2 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17b63d348819085668e3d9ac78ffa |
completed | April 29, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69eed2c32e8c8190b73bb9965ed47d64 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:28 p.m.