Triple
T27829838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sven (younger reindeer herd in Frozen II) |
E703062
|
entity |
| Predicate | hasSpeciesInFiction |
P180853
|
FINISHED |
| Object | reindeer |
—
|
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: reindeer | Statement: [Sven (younger reindeer herd in Frozen II), hasSpeciesInFiction, reindeer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeciesInFiction Context triple: [Sven (younger reindeer herd in Frozen II), hasSpeciesInFiction, reindeer]
-
A.
fictionalSpecies
Indicates that the subject is a species that exists only in fiction or imaginary works, rather than in real life.
-
B.
hasFictionalInhabitants
Indicates that a place or setting is inhabited by fictional or imaginary beings.
-
C.
hasFictionalType
Indicates that an entity is associated with or classified under a particular type or category that is fictional rather than real.
-
D.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
-
E.
hasRealityCounterpartInFiction
Indicates that a fictional element corresponds to or is based on a real-world counterpart within a work of fiction.
- 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_69ef840b94b08190950a4f77296938b2 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f757898fe48190b124dc7301672623 |
completed | May 3, 2026, 2:11 p.m. |
| PD | Predicate disambiguation | batch_69f754c484348190948d2a04ff228fb1 |
completed | May 3, 2026, 1:59 p.m. |
| PDg | Predicate description generation | batch_69f75788d40c819083bf2567b3091585 |
completed | May 3, 2026, 2:11 p.m. |
Created at: April 27, 2026, 5:55 p.m.