Triple
T32156758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buell Hall |
E821314
|
entity |
| Predicate | languageFocusOfOccupant |
P77291
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Buell Hall, languageFocusOfOccupant, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageFocusOfOccupant Context triple: [Buell Hall, languageFocusOfOccupant, French]
-
A.
fieldOfOccupant
Indicates the specific professional or academic field in which an occupant is engaged or associated.
-
B.
goalOfOccupant
Indicates that a particular goal or objective is associated with, pursued by, or intended for a specific occupant.
-
C.
stateOfFocus
chosen
Indicates the particular subject, area, or activity that an entity is currently concentrating attention or effort on.
-
D.
deviceFocus
Indicates that attention, control, or primary interaction is directed toward a particular device in a given context.
-
E.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
- 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_69f34905e098819082191a6922a6d607 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69ffc1550cb481908628e446d9b67f7b |
completed | May 9, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69ffc10a74708190ae90e2c378791f70 |
completed | May 9, 2026, 11:19 p.m. |
Created at: May 1, 2026, 12:32 a.m.