Triple
T32173624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valentine’s Day massacre in Harmony |
E821776
|
entity |
| Predicate | hasConsequencesInStory |
P40708
|
FINISHED |
| Object | trauma for the town of Harmony |
—
|
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: trauma for the town of Harmony | Statement: [Valentine’s Day massacre in Harmony, hasConsequencesInStory, trauma for the town of Harmony]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConsequencesInStory Context triple: [Valentine’s Day massacre in Harmony, hasConsequencesInStory, trauma for the town of Harmony]
-
A.
hasConsequence
Indicates that one event, action, or condition leads to or results in another as its outcome or effect.
-
B.
narrativeConsequence
chosen
Indicates that one event, action, or state occurs as a direct result or outcome of another within a narrative sequence.
-
C.
backstoryConsequence
Indicates that one event or situation occurs as a direct result or outcome of a character’s or entity’s prior history or background.
-
D.
hasConsequenceHypothesis
Indicates that one situation, event, or statement is hypothesized to lead to or imply a particular consequence.
-
E.
consequenceInText
Indicates that one event, action, or state is presented in the text as a consequence or result of another.
- 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:33 a.m.