Triple
T28103353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lumberjack Tavern |
E710294
|
entity |
| Predicate | associatedJudge |
P52405
|
FINISHED |
| Object | John D. Voelker |
—
|
NE NERFINISHED |
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: John D. Voelker | Statement: [Lumberjack Tavern, associatedJudge, John D. Voelker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedJudge Context triple: [Lumberjack Tavern, associatedJudge, John D. Voelker]
-
A.
associatedWithJudge
chosen
Indicates a relationship in which an entity has a professional, procedural, or contextual connection to a specific judge.
-
B.
judgeAlongside
Indicates that one entity serves as a judge together with another entity in the same evaluative context or proceeding.
-
C.
associatedWithCourt
Indicates a relationship in which an entity is linked or connected to a specific court, such as through jurisdiction, affiliation, or involvement in legal proceedings.
-
D.
hasJudgeFrom
Indicates that an entity has a judge whose origin, affiliation, or source is from a specified place or organization.
-
E.
judgeAppointmentBy
Indicates that one entity is appointed to the role of judging or evaluating another entity by a specific authority or process.
- 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_69ef9b71fdb081908b4a61cd7ff147c1 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_6a00b7fb90f881908f73edf2be8cc3a5 |
completed | May 10, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_6a00b75593d08190b3e76191cd79cdec |
completed | May 10, 2026, 4:50 p.m. |
Created at: April 27, 2026, 9:06 p.m.