Triple
T18370205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Howard Stambler |
E446161
|
entity |
| Predicate | alignmentWithProtagonist |
P130849
|
FINISHED |
| Object | antagonistic toward Michelle Burroughs |
—
|
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 toward Michelle Burroughs | Statement: [Howard Stambler, alignmentWithProtagonist, antagonistic toward Michelle Burroughs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentWithProtagonist Context triple: [Howard Stambler, alignmentWithProtagonist, antagonistic toward Michelle Burroughs]
-
A.
alignmentGoal
Indicates that an entity has a desired or target alignment state it aims to achieve or maintain.
-
B.
screenTimeRelativeToProtagonist
Indicates the amount of time a character appears on screen compared to the story’s main protagonist.
-
C.
alignedAgainst
Indicates that two or more entities are united in opposition to a common target, side, or objective.
-
D.
positionedAgainst
Indicates that one entity is placed so that it directly faces or is set opposite to another entity, often in close or contacting alignment.
-
E.
protagonistAllegiance
Indicates the group, cause, or side with which the main character is aligned or to which they show loyalty.
- 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_69d8b9f370b88190b1e5081c2c238e7f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51751e4288190873bcc4dc140ac16 |
completed | April 19, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69e44fed3fdc81908f4ed6a81db42416 |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a1bda48190a9cd1db436d4be62 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:44 a.m.