Triple
T1390298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Higgs field |
E29938
|
entity |
| Predicate | isNeutralUnder |
P28225
|
FINISHED |
| Object | strong interaction |
—
|
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: strong interaction | Statement: [Higgs field, isNeutralUnder, strong interaction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNeutralUnder Context triple: [Higgs field, isNeutralUnder, strong interaction]
-
A.
usesNeutral
Indicates that one entity employs or applies something in a neutral, unbiased, or non-aligned manner toward another entity or context.
-
B.
isNeutralSite
Indicates that a location serves as an impartial or non-aligned site for an interaction, event, or relationship between parties.
-
C.
neutralized
Indicates that one entity has rendered another entity ineffective, harmless, or no longer able to exert its intended effect.
-
D.
involvedNeutralPower
Indicates that a neutral party or state is involved in a situation, event, or interaction without taking a side or participating as a belligerent.
-
E.
hasNeutralPronoun
Indicates that an entity is referred to using a gender-neutral pronoun.
- 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_69a498dc92f8819094a1108f8ac90f43 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c35e023c8190b45688796d90534b |
completed | March 1, 2026, 10:53 p.m. |
| PD | Predicate disambiguation | batch_69a4beffcf808190ab4cd0271257ce63 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c2f16ae081908c92792253f3eb4b |
completed | March 1, 2026, 10:51 p.m. |
Created at: March 1, 2026, 7:59 p.m.