Triple
T29694129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type I string theory |
E751295
|
entity |
| Predicate | hasMasslessClosedStringSector |
P199908
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Type I string theory, hasMasslessClosedStringSector, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMasslessClosedStringSector Context triple: [Type I string theory, hasMasslessClosedStringSector, yes]
-
A.
hasMassTerm
Indicates that one entity is classified as a mass (uncountable) term associated with another entity.
-
B.
isNonSupersymmetric
Indicates that the entity does not exhibit or obey supersymmetry, i.e., it lacks a symmetry relating bosons and fermions.
-
C.
hasD0Branes
Indicates that an entity possesses or is associated with D0-branes (point-like D-branes) in a given physical or theoretical context.
-
D.
hasBosonicWorldvolumeFields
Indicates that the subject possesses or is associated with bosonic fields defined on its worldvolume.
-
E.
isMasslessIn
Indicates that an entity has zero rest mass within a specified context, system, or environment.
- 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_69f0d625b09481909b0b69aea1e846c8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
| PDg | Predicate description generation | batch_69ff63e5c35081908f69ac44e12b8f52 |
completed | May 9, 2026, 4:42 p.m. |
Created at: April 28, 2026, 7:19 p.m.