Triple
T31164078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian Gibbons |
E794424
|
entity |
| Predicate | activeYearsWithStart |
P34676
|
FINISHED |
| Object | late 1970s |
—
|
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: late 1970s | Statement: [Ian Gibbons, activeYearsWithStart, late 1970s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activeYearsWithStart Context triple: [Ian Gibbons, activeYearsWithStart, late 1970s]
-
A.
activeYearsWith
Indicates the span of time during which an entity was actively engaged in a particular role, activity, or association with another entity.
-
B.
activeYearsEndTime
Indicates the point in time when an entity’s period of activity or operation comes to an end.
-
C.
activeInYears
chosen
Indicates that an entity was active or operational during the specified years or year range.
-
D.
activeYearsInCareer
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
E.
activeYearsPeak
Indicates the span of years during which an entity was at the height of its activity or prominence.
- 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_69f224d504908190b01278dcb7fc3fa7 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 29, 2026, 9:07 p.m.