Triple
T2911554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jericho-Trompete siren |
E63692
|
entity |
| Predicate | effectOnEnemy |
P8792
|
FINISHED |
| Object | induce fear |
—
|
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: induce fear | Statement: [Jericho-Trompete siren, effectOnEnemy, induce fear]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnEnemy Context triple: [Jericho-Trompete siren, effectOnEnemy, induce fear]
-
A.
effectOnSystem
Indicates the influence, change, or impact that one entity, action, or condition has on the state or behavior of a system.
-
B.
effectOfDeath
Indicates the causal impact or consequences that a death has on another entity, state, or process.
-
C.
effectOnShips
Indicates the impact or influence that one entity, event, or condition has on ships.
-
D.
targetsAsRacialEnemy
Indicates that one party identifies and treats another party as an enemy specifically on the basis of their race.
-
E.
involvedPhysicalEffect
chosen
Indicates that one entity participates in causing, experiencing, or mediating a physical effect on another entity or the environment.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0ea0ae4819096f17d74072b0b78 |
completed | March 7, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69abdd1b77608190b20fc078fdb85e64 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:11 p.m.