Triple
T23726419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coalinga State Hospital |
E586289
|
entity |
| Predicate | legalStatusOfPatients |
P153723
|
FINISHED |
| Object | civil commitment |
—
|
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: civil commitment | Statement: [Coalinga State Hospital, legalStatusOfPatients, civil commitment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legalStatusOfPatients Context triple: [Coalinga State Hospital, legalStatusOfPatients, civil commitment]
-
A.
legalStatusInMostCountries
Indicates the typical legal classification or treatment of something across the majority of countries.
-
B.
legalStatusVariesBy
Indicates that the legal status of something differs depending on a specified jurisdiction, context, or set of conditions.
-
C.
legalCodeStatus
Indicates the legal or regulatory status assigned to a specific code within a legal or statutory system (e.g., active, repealed, pending).
-
D.
legalStatusClarifiedBy
Indicates that the legal status of something is defined, explained, or resolved by a specific document, decision, or authoritative act.
-
E.
legalStatusOfVictims
Indicates the legal classification or condition of the victims in relation to the event or action described.
- 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_69e24906fb108190a6898751e46bdc11 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b915a888819088e92f99711e8120 |
completed | April 29, 2026, 7:53 a.m. |
| PD | Predicate disambiguation | batch_69f155e4b1148190836ede4741dcb888 |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f15b453da88190889a8d9b21727958 |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 17, 2026, 7:08 p.m.