Triple
T32655439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bamford & Martin Ltd. |
E834847
|
entity |
| Predicate | has notable employee |
P304
|
FINISHED |
| Object | Lionel Martin |
—
|
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: Lionel Martin | Statement: [Bamford & Martin Ltd., has notable employee, Lionel Martin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: has notable employee Context triple: [Bamford & Martin Ltd., has notable employee, Lionel Martin]
-
A.
notableEmployerFeature
Indicates that an employer is distinguished or recognized for a particular characteristic, quality, or attribute.
-
B.
notableEmployer
Indicates that an entity has been employed by, or has worked for, a particularly significant or noteworthy organization or individual.
-
C.
hasNotableMember
chosen
Indicates that a group, organization, or collection includes at least one member who is distinguished or noteworthy in some significant way.
-
D.
notableWorker
Indicates that the subject is a worker who is distinguished or recognized for being particularly important, prominent, or exemplary in their work.
-
E.
hasEmployees
Indicates that one entity employs one or more other entities as its workers or staff.
- 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_69f3492f72248190ba42fa596aea50e1 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c77b504c8190aa225fad8f2cb2aa |
completed | May 3, 2026, 3:56 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:08 a.m.