Triple
T28624305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlisle Military Academy |
E724475
|
entity |
| Predicate | predecessorInLocationOf |
P180319
|
FINISHED |
| Object | Arlington State College |
—
|
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: Arlington State College | Statement: [Carlisle Military Academy, predecessorInLocationOf, Arlington State College]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorInLocationOf Context triple: [Carlisle Military Academy, predecessorInLocationOf, Arlington State College]
-
A.
predecessorLocatedAt
Indicates that the location specified was the place where the immediately preceding version, state, or instance of an entity was situated.
-
B.
predecessorInRole
Indicates that one entity previously held a particular role or position that was later occupied by another entity.
-
C.
predecessor
Indicates that one entity comes before another in an ordered sequence or succession.
-
D.
predecessorArea
Indicates that one area previously existed or was defined before another area in a sequence or versioning of areas.
-
E.
predecessorGround
Indicates that one entity serves as the immediate prior version or state of another entity within a sequence or process.
- 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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
| PDg | Predicate description generation | batch_69f73adfd9a081908adae6bd59dfefb9 |
completed | May 3, 2026, 12:09 p.m. |
Created at: April 28, 2026, 4:35 a.m.