Triple
T28306859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Truth Be Told |
E713879
|
entity |
| Predicate | leadCharacterCoverEmployer |
P93486
|
FINISHED |
| Object | Credit Dauphine |
—
|
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: Credit Dauphine | Statement: [Truth Be Told, leadCharacterCoverEmployer, Credit Dauphine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterCoverEmployer Context triple: [Truth Be Told, leadCharacterCoverEmployer, Credit Dauphine]
-
A.
namedForEmployer
Indicates that an entity is named after, or in honor of, its employer.
-
B.
employerInPlot
chosen
Indicates that one entity serves as the employer of another within the context of a specific plot or storyline.
-
C.
employerIn
Indicates that one entity serves as the employer of another within a specified context, such as a location, organization, or time period.
-
D.
employerOfNotablePerson
Indicates that an entity serves or has served as the employer of a person who is considered notable.
-
E.
workCharacter
Indicates that a person is a fictional or narrative character appearing in a particular creative work.
- 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_69efb5256afc8190b9322d25c3ae6320 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f644de4a84819087ddb84757fc4585 |
completed | May 2, 2026, 6:39 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:38 p.m.