Triple
T1372822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bowditch School (Boston) |
E30151
|
entity |
| Predicate | hasNamesakeOccupation |
P365
|
FINISHED |
| Object | mathematician |
—
|
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: mathematician | Statement: [Bowditch School (Boston), hasNamesakeOccupation, mathematician]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNamesakeOccupation Context triple: [Bowditch School (Boston), hasNamesakeOccupation, mathematician]
-
A.
namesakeOccupation
chosen
Indicates that one entity’s occupation is the same as, or derived from, the occupation associated with the other entity’s namesake.
-
B.
namedPersonOccupation
Indicates that a person is explicitly identified as having a particular occupation or job role.
-
C.
hasFamousNamesakeRole
Indicates that an entity has a role or position that shares its name with a well-known or historically notable person.
-
D.
notableOccupationContext
Indicates that the referenced occupation is notable or significant specifically within the given contextual framework or domain.
-
E.
occupationOf
Indicates that one entity holds or performs the job, role, or profession associated with another entity.
- 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_69a498f912008190a376a98b207b2071 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c2f4889881908103473a0173e23f |
completed | March 1, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69a4befcabdc8190a9f05d002603f81c |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:57 p.m.