Triple
T33853636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holly Body |
E867703
|
entity |
| Predicate | associatedWithYearOfWork |
P133441
|
FINISHED |
| Object | 1984 |
—
|
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: 1984 | Statement: [Holly Body, associatedWithYearOfWork, 1984]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithYearOfWork Context triple: [Holly Body, associatedWithYearOfWork, 1984]
-
A.
associatedWithWorkOf
Indicates that one entity has a connection or involvement with the work, creation, or output produced by another entity.
-
B.
associatedWithYearFilm
Indicates a relationship where something (such as an event, award, or record) is linked to or pertains to a specific film released or identified in a given year.
-
C.
yearAssociated
chosen
Indicates a specific year that is relevant or linked to an entity, event, or relationship (such as the year it occurred, was created, or is otherwise associated).
-
D.
associatedClassYear
Indicates a relationship linking an entity to the specific academic class year with which it is connected or identified.
-
E.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
- 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_69f349937b648190a34ada70f6a2b534 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:47 a.m.