Triple
T1246742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Happy Chandler |
E26782
|
entity |
| Predicate | startTimeAsUnitedStatesSenator |
P25747
|
FINISHED |
| Object | 1939 |
—
|
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: 1939 | Statement: [Happy Chandler, startTimeAsUnitedStatesSenator, 1939]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTimeAsUnitedStatesSenator Context triple: [Happy Chandler, startTimeAsUnitedStatesSenator, 1939]
-
A.
startTimeAsUSCongressSeat
Indicates the date and time at which an individual officially begins serving in a specific seat in the U.S. Congress.
-
B.
startTimeOfPoliticalCareer
Indicates the point in time when an individual’s political career officially began.
-
C.
startTimeAsFedGovernor
Indicates the date and time at which an individual began serving in the role of Federal Reserve Governor.
-
D.
startTimeAsGovernorOfIndiana
Indicates the date and time at which an individual began serving as the governor of Indiana.
-
E.
succeededInOfficeAsSenatorFromNewYorkBy
Indicates that one individual was succeeded in the role of Senator from New York by another individual.
- F. None of above. chosen
Provenance (4 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf6750a48190b86e9248ed54d90a |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6b075881908e867c25b5080e25 |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bc49693c8190978ec63a5171d342 |
completed | March 1, 2026, 10:23 p.m. |
Created at: March 1, 2026, 7:47 p.m.