Triple
T12043963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frank E. Brown’s townsite name "Moreno" |
E286735
|
entity |
| Predicate | associatedWithOccupationOfNamer |
P35215
|
FINISHED |
| Object | civil engineer |
—
|
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: civil engineer | Statement: [Frank E. Brown’s townsite name "Moreno", associatedWithOccupationOfNamer, civil engineer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithOccupationOfNamer Context triple: [Frank E. Brown’s townsite name "Moreno", associatedWithOccupationOfNamer, civil engineer]
-
A.
occupationalAssociation
Indicates a relationship where one entity is connected to another through a job, profession, or work-related role.
-
B.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
-
C.
associatedNicknameOfWork
Indicates that a given nickname or informal title is commonly used to refer to a particular work.
-
D.
occupationalNameFor
Indicates that one entity is the name or label used to denote the occupation or profession of another entity.
-
E.
isAssociatedWithProfessionOfBearer
chosen
Indicates that one entity is connected to, or involved with, the profession or occupational role held by 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.