Triple
T30943341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fragile Express |
E788319
|
entity |
| Predicate | blamedForInFiction |
P170823
|
FINISHED |
| Object | destruction of South Knot City |
—
|
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: destruction of South Knot City | Statement: [Fragile Express, blamedForInFiction, destruction of South Knot City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: blamedForInFiction Context triple: [Fragile Express, blamedForInFiction, destruction of South Knot City]
-
A.
responsibleForFictional
Indicates that one entity bears responsibility for creating, managing, or causing a fictional work, character, event, or universe associated with another entity.
-
B.
fictionalAuthorVictim
Indicates that one entity is the author of a fictional work in which the other entity appears as a victim.
-
C.
associatedWithCaseInFiction
Indicates that an entity is connected to, involved in, or relevant to a particular case or investigation within a fictional context.
-
D.
guardedByInFiction
Indicates that one fictional entity is protected or watched over by another within a narrative context.
-
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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f695f9fe7c819084322bf6cdc70a13 |
completed | May 3, 2026, 12:25 a.m. |
| PD | Predicate disambiguation | batch_69f690ed5d008190831cf8e44cce28af |
completed | May 3, 2026, 12:03 a.m. |
| PDg | Predicate description generation | batch_69f695385a2881908cc28ef97fffc867 |
completed | May 3, 2026, 12:22 a.m. |
Created at: April 29, 2026, 8:53 p.m.