Triple
T5702289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maureen Dowd |
E125691
|
entity |
| Predicate | startedWorkingAtTheNewYorkTimes |
P4697
|
FINISHED |
| Object | 1983 |
—
|
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: 1983 | Statement: [Maureen Dowd, startedWorkingAtTheNewYorkTimes, 1983]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startedWorkingAtTheNewYorkTimes Context triple: [Maureen Dowd, startedWorkingAtTheNewYorkTimes, 1983]
-
A.
occupationBegan
chosen
Indicates the point in time when an entity started holding a particular occupation or job.
-
B.
editorStartTimeAtNewsOfTheWorld
Indicates the time at which an individual began serving as an editor at the publication "News of the World."
-
C.
becameFreeNewspaper
Indicates that an entity transitioned from a paid or different status to being distributed as a free newspaper.
-
D.
hadNewspaper
Indicates that an entity possessed or was in ownership of a newspaper at a particular time.
-
E.
timeInOfficeBeginsIn
Indicates the point in time or date when an entity’s term, tenure, or period in office starts.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0245581988190a819b8137533ed31 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.