Triple
T36944495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Tanner |
E913866
|
entity |
| Predicate | hasAlternateIdentity |
P108643
|
FINISHED |
| Object | Don Juan (in the dream sequence Don Juan in Hell) |
—
|
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: Don Juan (in the dream sequence Don Juan in Hell) | Statement: [John Tanner, hasAlternateIdentity, Don Juan (in the dream sequence Don Juan in Hell)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateIdentity Context triple: [John Tanner, hasAlternateIdentity, Don Juan (in the dream sequence Don Juan in Hell)]
-
A.
hasMultipleIdentities
chosen
Indicates that a single entity is associated with more than one distinct identity or persona.
-
B.
alternativeIdentification
Indicates that one entity serves as an alternative identifier or reference for another entity.
-
C.
hasNumberOfIdentities
Indicates the count of distinct identities associated with a given entity.
-
D.
hasFormerIdentity
Indicates that an entity previously had a different identity, name, or role before its current one.
-
E.
hasIdentity
Indicates that one entity is the same as, or is identified as, another specific entity or identifier.
- 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_69f76e8a6a5c81909c1febf32bf3fe23 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fe610e1f6881908f10070ba64643cf |
completed | May 8, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69fe604c6c008190ad659e9b9fa82f7b |
completed | May 8, 2026, 10:14 p.m. |
Created at: May 3, 2026, 4:13 p.m.