Triple
T34370485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marshall |
E882136
|
entity |
| Predicate | relatedOccupationTerm |
P136370
|
FINISHED |
| Object | marshal |
—
|
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: marshal | Statement: [Marshall, relatedOccupationTerm, marshal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedOccupationTerm Context triple: [Marshall, relatedOccupationTerm, marshal]
-
A.
relatedProfession
Indicates that two entities have professions that are connected or associated in some meaningful way, such as being in the same field, industry, or professional domain.
-
B.
occupationalAssociation
Indicates a relationship where one entity is connected to another through a job, profession, or work-related role.
-
C.
aliasOfOccupation
chosen
Indicates that one occupation term is an alternative name or alias for another occupation.
-
D.
relatedCommunityOccupation
Indicates that an entity has an occupation or role that is associated with, serves, or is otherwise connected to a particular community.
-
E.
involvedOccupationOf
Indicates that an entity participates in or is associated with a particular occupation or professional role.
- 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_69f349bf5d7481908dd5da4cbdf74047 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fbe4a08190bfe65ebd141164e9 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:59 a.m.