Triple
T36322384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolours Price |
E894370
|
entity |
| Predicate | gaveInterviewTo |
P40000
|
FINISHED |
| Object | Boston College oral history project |
—
|
NE NERFINISHED |
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: Boston College oral history project | Statement: [Dolours Price, gaveInterviewTo, Boston College oral history project]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gaveInterviewTo Context triple: [Dolours Price, gaveInterviewTo, Boston College oral history project]
-
A.
gaveInterviewsAbout
Indicates that an entity conducted interviews whose subject or topic was another specified entity.
-
B.
interviewedBy
chosen
Indicates that an entity is the subject of an interview conducted by another entity.
-
C.
hasGivenInterviewsIn
Indicates that an entity has conducted or participated in interviews within a specified place or context.
-
D.
usesInterviews
Indicates that one entity employs interviews as a method or tool in relation to another entity or process.
-
E.
hasInterviews
Indicates that one entity conducts, contains, or is associated with interviews involving 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_69f76e4d1a788190a6ab6ccca28547a7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7ba6d06f48190a71b5a2f19e2232f |
completed | May 3, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a4aad48190a62e41c5e39339d9 |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:09 p.m.