Triple
T2296997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haverhill Academy |
E51639
|
entity |
| Predicate | hasAlumnusOccupation |
P4387
|
FINISHED |
| Object | poet |
—
|
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: poet | Statement: [Haverhill Academy, hasAlumnusOccupation, poet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlumnusOccupation Context triple: [Haverhill Academy, hasAlumnusOccupation, poet]
-
A.
hasAlumni
Indicates that an institution or organization is associated with individuals who formerly attended or graduated from it.
-
B.
hasNotableAlumniType
chosen
Indicates that an entity has notable alumni belonging to a specified category or type.
-
C.
hasAlumniNetwork
Indicates that an entity maintains or is associated with an organized network or community of its former members or graduates.
-
D.
positionOfNotableAlumnus
Indicates the professional role or office held by a notable alumnus in relation to an institution or organization.
-
E.
hasAlumniWhoWon
Indicates that an institution has alumni who have won a particular award, honor, or competition.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:49 p.m.