Triple
T25148157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyder |
E629994
|
entity |
| Predicate | isUsedByFictionalCharacter |
P62301
|
FINISHED |
| Object | Sufiya Zinobia |
—
|
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: Sufiya Zinobia | Statement: [Hyder, isUsedByFictionalCharacter, Sufiya Zinobia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUsedByFictionalCharacter Context triple: [Hyder, isUsedByFictionalCharacter, Sufiya Zinobia]
-
A.
wornByFictionalCharacter
Indicates that a particular item (such as clothing or accessories) is worn by a specific fictional character.
-
B.
ownedByFictionalCharacter
chosen
Indicates that something is possessed or owned by a fictional (not real-world) character.
-
C.
isFictionalCharacter
Indicates that the subject is a character that exists only in fiction rather than in real life.
-
D.
usedInFictionalWork
Indicates that something (such as a concept, object, or character) appears or is employed within a specific fictional work.
-
E.
employsFictionalCharacter
Indicates that one entity (typically an organization or individual) has hired or uses the services of a fictional character in some capacity.
- 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_69e2ff349e408190a6f4a5a66279f54d |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f4684e47988190a5c0639fc7fc21e8 |
completed | May 1, 2026, 8:46 a.m. |
| PD | Predicate disambiguation | batch_69f44d8043b081908bbffd7f044b4f26 |
completed | May 1, 2026, 6:51 a.m. |
Created at: April 18, 2026, 6:30 a.m.