Triple
T15156602
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nixon v. Herndon |
E362095
|
entity |
| Predicate | plaintiffOccupation |
P2374
|
FINISHED |
| Object | physician |
—
|
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: physician | Statement: [Nixon v. Herndon, plaintiffOccupation, physician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: plaintiffOccupation Context triple: [Nixon v. Herndon, plaintiffOccupation, physician]
-
A.
defendantProfession
Indicates the professional occupation or job role held by the defendant in a legal case.
-
B.
allegedOccupation
Indicates that one entity is claimed or reported to be the occupation or job role of another entity, without asserting that this claim is necessarily true.
-
C.
defendantOccupationAtTime
Indicates that a defendant held a particular occupation or job role during a specified time period.
-
D.
subjectOccupation
chosen
Indicates that the subject holds or performs a particular job, profession, or role as their occupation.
-
E.
proposerOccupation
Indicates the occupation or professional role held by the entity acting as the proposer in a given context.
- 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_69d85a0759908190b8a051d2e2a1cbe6 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0060c62b08190bcdbd912d011d1ba |
completed | April 15, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69deb9779acc81908ed2dad382c42dca |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:08 a.m.