Triple
T31280704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diane Lockhart |
E797659
|
entity |
| Predicate | worksAtFictionalFirm |
P109189
|
FINISHED |
| Object | Lockhart/Gardner |
—
|
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: Lockhart/Gardner | Statement: [Diane Lockhart, worksAtFictionalFirm, Lockhart/Gardner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksAtFictionalFirm Context triple: [Diane Lockhart, worksAtFictionalFirm, Lockhart/Gardner]
-
A.
worksForFictionalOrganization
chosen
Indicates that an entity is employed by or affiliated as a worker with a fictional organization.
-
B.
workAt
Indicates that an entity is employed by or performs work for a particular organization, company, or place.
-
C.
hasFictionalCorporation
Indicates that an entity is associated with or includes a fictional corporation within its content, setting, or narrative.
-
D.
hasFictionalLawFirm
Indicates that an entity is associated with or employs a law firm that exists only within a fictional or narrative context.
-
E.
fictionalCorporation
Indicates that an entity is a corporation that exists only in fiction rather than in the real world.
- 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_69f224def9088190a37034eab3daf57f |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 29, 2026, 9:13 p.m.