Triple
T35187611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hobbes |
E1016030
|
entity |
| Predicate | isStuffedAnimalWithinFiction |
P182369
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hobbes, isStuffedAnimalWithinFiction, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isStuffedAnimalWithinFiction Context triple: [Hobbes, isStuffedAnimalWithinFiction, true]
-
A.
isFictionalCharacter
Indicates that the subject is a character that exists only in fiction rather than in real life.
-
B.
hasFictionalAgriculturalCharacter
Indicates that an entity features or includes a character associated with agriculture within a fictional context.
-
C.
hasSpeciesInFiction
Indicates that a fictional work or universe features a particular species as part of its narrative or setting.
-
D.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
E.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
- F. None of above. chosen
Provenance (4 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_69f76ddd815c8190b822eea06630f9fb |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78dc3776c8190bbd4702acd5a191e |
completed | May 3, 2026, 6:02 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c337cec8190bfdab225a3cc96db |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.