Triple
T926967
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judge Danforth |
E20004
|
entity |
| Predicate | positionInCourt |
P22449
|
FINISHED |
| Object | deputy governor of Massachusetts Bay Colony |
—
|
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: deputy governor of Massachusetts Bay Colony | Statement: [Judge Danforth, positionInCourt, deputy governor of Massachusetts Bay Colony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionInCourt Context triple: [Judge Danforth, positionInCourt, deputy governor of Massachusetts Bay Colony]
-
A.
positionInCase
Indicates the specific role, status, or placement that an entity holds within a particular case or legal proceeding.
-
B.
positionInLineup
Indicates the specific ordered place an entity occupies within a lineup or sequence of entities.
-
C.
playingPosition
Indicates the specific role or position an individual occupies while participating in a game or sport.
-
D.
positionB
Indicates that one entity occupies or is located at a specific position relative to another entity.
-
E.
playsInPosition
Indicates that an entity (typically a player) performs or operates in a specific role or position within a game, sport, or activity.
- 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_69a493af3dc48190adb7263e6e445ea1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b388f0bc8190a087222636135ba5 |
completed | March 1, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69a4b2970a4c8190b22cb2fd4706f62b |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b385176081909e3e8c3f647c1fd4 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:40 p.m.