Triple
T35570657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iggy Frome |
E1027924
|
entity |
| Predicate | seriesSettingInstitutionType |
P303
|
FINISHED |
| Object | public hospital |
—
|
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: public hospital | Statement: [Iggy Frome, seriesSettingInstitutionType, public hospital]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seriesSettingInstitutionType Context triple: [Iggy Frome, seriesSettingInstitutionType, public hospital]
-
A.
settingInstitution
Indicates that an entity is associated with or occurs within a particular institution that serves as its setting or context.
-
B.
institutionalSeriesOf
Indicates that one entity is part of, or belongs to, a series of institutional items or events organized or maintained by another entity.
-
C.
typeOfInstitution
chosen
Indicates the specific kind or category of institution that an entity belongs to or is classified as.
-
D.
governsInstitutionType
Indicates that an entity has authoritative control or regulatory oversight over a particular type or category of institution.
-
E.
typeOfInstitutionNetwork
Indicates a relationship where an institution is classified as belonging to a particular type or category of institutional network.
- 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_69f76e0386688190b931bacdc145938c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
Created at: May 3, 2026, 4:04 p.m.