Triple
T1070404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pennsylvania Military College |
E23312
|
entity |
| Predicate | hadResidentialProgram |
P23936
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pennsylvania Military College, hadResidentialProgram, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadResidentialProgram Context triple: [Pennsylvania Military College, hadResidentialProgram, yes]
-
A.
reconstructedWithAidProgram
Indicates that an entity was rebuilt or restored through the support or resources provided by an aid program.
-
B.
establishedProgram
Indicates that an entity has created and put into operation a formal program that is now in an active, ongoing state.
-
C.
residence
Indicates that one entity lives at, is based in, or habitually occupies the location represented by the other entity.
-
D.
hadEvent
Indicates that an entity experienced, hosted, or was associated with a specific event at some point in time.
-
E.
hadMeetingHouse
Indicates that an entity possessed or was associated with a specific meeting house as a place for gatherings or assemblies.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92848148190ba8795cb8d0a1d0a |
completed | March 1, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69a4b73844708190a16c9e9824ca2fb6 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b8d5076481908640a0d873efdf14 |
completed | March 1, 2026, 10:08 p.m. |
Created at: March 1, 2026, 7:42 p.m.