Triple
T19383401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weedon Scott |
E484868
|
entity |
| Predicate | inUniverseProfessionDetail |
P124907
|
FINISHED |
| Object | mining expert for a mining company |
—
|
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: mining expert for a mining company | Statement: [Weedon Scott, inUniverseProfessionDetail, mining expert for a mining company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inUniverseProfessionDetail Context triple: [Weedon Scott, inUniverseProfessionDetail, mining expert for a mining company]
-
A.
memberProfession
Indicates that a member or individual holds or practices a particular profession or occupation.
-
B.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
-
C.
inUniverseWorkplaceRole
chosen
Indicates that an entity holds a specific workplace role or job position within a fictional or narrative universe.
-
D.
leftProfession
Indicates that an entity has stopped or abandoned a particular profession or occupation they previously held.
-
E.
representsProfessionIn
Indicates that an entity holds or is associated with a particular profession within a specified context, domain, or location.
- 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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61a626b288190a27a30deb0ccabc3 |
completed | April 20, 2026, 12:21 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:35 p.m.