Triple
T13519123
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord Wessex |
E322846
|
entity |
| Predicate | alignmentInNarrative |
P74485
|
FINISHED |
| Object | antagonistic |
—
|
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: antagonistic | Statement: [Lord Wessex, alignmentInNarrative, antagonistic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentInNarrative Context triple: [Lord Wessex, alignmentInNarrative, antagonistic]
-
A.
alignmentInStory
chosen
Indicates how a character’s moral or ethical stance (e.g., good, neutral, evil) is portrayed within the context of a specific story.
-
B.
alignmentAtIntroduction
Indicates that two entities share a particular alignment or stance at the moment one is first introduced.
-
C.
narrativeStrategy
Indicates the method or approach used to structure, present, or convey a story or sequence of events.
-
D.
narrativeConnection
Indicates a meaningful relationship between elements within a narrative, such as events, characters, or scenes, that links them in terms of plot, causality, or thematic continuity.
-
E.
narrativeSequence
Indicates that one event or narrative element follows another in a temporal or logical storytelling order.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa27f048190bed33a98e28c8d09 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:44 p.m.