Triple
T34063512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cath Hardacre |
E873559
|
entity |
| Predicate | createsFalseIdentityAs |
P149778
|
FINISHED |
| Object | doctor |
—
|
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: doctor | Statement: [Cath Hardacre, createsFalseIdentityAs, doctor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: createsFalseIdentityAs Context triple: [Cath Hardacre, createsFalseIdentityAs, doctor]
-
A.
fakeIDName
chosen
Indicates that one entity uses or is associated with a false or fraudulent identification name in relation to another entity or context.
-
B.
usedFalseIdentityInBurial
Indicates that a person employed a false or assumed identity in the context of a burial, such as during funeral arrangements, documentation, or interment.
-
C.
unawareOfTrueIdentityOf
Indicates that one entity does not know or recognize the real or actual identity of another entity.
-
D.
contrastsWithTrueIdentity
Indicates that something is presented or perceived in a way that differs from, or is in opposition to, its true underlying identity.
-
E.
falseFor
Indicates that a given statement or proposition does not hold true or is invalid specifically in the context of the referenced entity or situation.
- 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_69f349a4af208190afa14888f9c9fb9d |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff38b960808190a8263348f1e5c0e4 |
completed | May 9, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69ff37d97d9c8190849b2bac14f9af1d |
completed | May 9, 2026, 1:34 p.m. |
Created at: May 1, 2026, 1:52 a.m.