Triple
T5042333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terror in a Texas Town |
E113572
|
entity |
| Predicate | leadCharacterOrigin |
P28569
|
FINISHED |
| Object | Swedish immigrant |
—
|
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: Swedish immigrant | Statement: [Terror in a Texas Town, leadCharacterOrigin, Swedish immigrant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterOrigin Context triple: [Terror in a Texas Town, leadCharacterOrigin, Swedish immigrant]
-
A.
characterOrigin
Indicates the source, background, or initial context from which a character originates.
-
B.
protagonistOrigin
chosen
Indicates that one entity is the origin, source, or starting point of the protagonist in a narrative or story.
-
C.
introducedByCharacter
Indicates that one character is responsible for presenting, bringing into the story, or otherwise causing another entity to be first revealed or made known.
-
D.
leadCharacterStatus
Indicates the role or condition of an entity when it serves as the primary or central character in a narrative or context.
-
E.
characterIn
Indicates that an entity appears as a character within a specified work, story, or narrative.
- 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_69bd44384298819089c49e7c330ec7b8 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd73df8f7481909a8b86c4ae69aab9 |
completed | March 20, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69bd71529d608190a53470ba6c14bb1d |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:37 p.m.