Triple
T25654473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Halla |
E643193
|
entity |
| Predicate | opposedToInFiction |
P97499
|
FINISHED |
| Object | Shundi |
—
|
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: Shundi | Statement: [Halla, opposedToInFiction, Shundi]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opposedToInFiction Context triple: [Halla, opposedToInFiction, Shundi]
-
A.
opposesFictional
chosen
Indicates that one fictional entity is in opposition or conflict with another within a narrative or imagined context.
-
B.
basedOnInFiction
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
-
C.
fictionalCounterpartIn
Indicates that one entity serves as a fictional analogue or stand-in for another entity within a specified work or fictional universe.
-
D.
worksInFictionalContext
Indicates that an entity performs work or fulfills a role within a fictional or imagined setting rather than in real-world circumstances.
-
E.
responsibleForFictional
Indicates that one entity bears responsibility for creating, managing, or causing a fictional work, character, event, or universe associated with another entity.
- 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_69e77e7d8a848190a98d0162325fd780 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6456608190b94e7c2e2c2a4824 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 21, 2026, 6:31 p.m.