Triple
T34105428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | W71 warhead |
E874691
|
entity |
| Predicate | effectEmphasis |
P192799
|
FINISHED |
| Object | X-ray output |
—
|
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: X-ray output | Statement: [W71 warhead, effectEmphasis, X-ray output]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectEmphasis Context triple: [W71 warhead, effectEmphasis, X-ray output]
-
A.
hasEmphasis
Indicates that one element is given special stress, importance, or prominence relative to others.
-
B.
matchTypeEmphasis
Indicates that one entity emphasizes or highlights a particular type or category of match in relation to another entity.
-
C.
emotionEffect
Indicates that one entity’s emotional state causes or influences a change in another entity’s feelings, behavior, or condition.
-
D.
designEmphasizes
Indicates that a design intentionally places special importance or focus on a particular feature, principle, or aspect over others.
-
E.
expressivePower
Indicates the degree to which one system, language, or formalism can represent or capture the behaviors, structures, or concepts expressible in another.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd2a215d6c8190a1a428ccaee603f1 |
completed | May 8, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69fd28ef19688190bb8370f2812a43e7 |
completed | May 8, 2026, 12:06 a.m. |
| PDg | Predicate description generation | batch_69fd2a2095f88190bfcbcb2973516ffc |
completed | May 8, 2026, 12:11 a.m. |
Created at: May 1, 2026, 1:53 a.m.