Triple
T28218969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runaway Horses |
E711396
|
entity |
| Predicate | hasRecurrentCharacter |
P141621
|
FINISHED |
| Object | Shigekuni Honda |
—
|
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: Shigekuni Honda | Statement: [Runaway Horses, hasRecurrentCharacter, Shigekuni Honda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurrentCharacter Context triple: [Runaway Horses, hasRecurrentCharacter, Shigekuni Honda]
-
A.
hasRecurringCharacterFrom
Indicates that one work or series includes a character who also appears recurrently in another work or series.
-
B.
hasRepetition
Indicates that something occurs, appears, or is performed more than once, showing recurrence or repeated instances within a given context.
-
C.
isRecurringCharacter
chosen
Indicates that an entity appears repeatedly or regularly within a given narrative, series, or context rather than only once.
-
D.
hasCharacterSequence
Indicates that one entity contains, exhibits, or follows a specific ordered sequence of characters.
-
E.
usesRepetition
Indicates that one entity employs repeated elements, actions, or patterns as a deliberate feature or technique in relation to another entity or context.
- 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69ff397e19a88190a945b826159f5290 |
completed | May 9, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69ff392400d0819088d30d08d4a774bd |
completed | May 9, 2026, 1:39 p.m. |
Created at: April 27, 2026, 10:45 p.m.