Triple
T1128743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | G. Gordon Liddy |
E24778
|
entity |
| Predicate | activeYearsInBroadcasting |
P18004
|
FINISHED |
| Object | 1992-2012 |
—
|
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: 1992-2012 | Statement: [G. Gordon Liddy, activeYearsInBroadcasting, 1992-2012]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: activeYearsInBroadcasting Context triple: [G. Gordon Liddy, activeYearsInBroadcasting, 1992-2012]
-
A.
activeYearsInCareer
chosen
Indicates the span of time during which an entity was actively engaged in a particular career or professional field.
-
B.
activeYearsInFilm
Indicates the span of years during which an entity was actively involved in film-related work or roles.
-
C.
activeYearsInSport
Indicates the span of years during which an entity actively participated in a particular sport.
-
D.
activeInYear
Indicates that an entity was active, functioning, or operational during a specified year.
-
E.
historicallyActiveIn
Indicates that an entity was active or engaged in significant activities within a particular place or context during a past historical period.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb48de2081909a0dce005b1c9df1 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.