Triple
T29694208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M5-branes |
E751297
|
entity |
| Predicate | fluxQuantization |
P9520
|
FINISHED |
| Object | 4-form flux on S4 proportional to number of M5-branes |
—
|
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: 4-form flux on S4 proportional to number of M5-branes | Statement: [M5-branes, fluxQuantization, 4-form flux on S4 proportional to number of M5-branes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fluxQuantization Context triple: [M5-branes, fluxQuantization, 4-form flux on S4 proportional to number of M5-branes]
-
A.
quantizationIs
Indicates that one entity is a specific quantization or discretized representation of another entity.
-
B.
quantizationLeadsTo
Indicates that the process or property of quantization causes, results in, or gives rise to another state, effect, or outcome.
-
C.
isQuantumOf
chosen
Indicates that one entity represents a discrete, indivisible unit or packet of the other entity in a quantized relationship.
-
D.
quantizationRequires
Indicates that performing quantization on one entity depends on or necessitates the use, presence, or completion of another entity.
-
E.
quantizationType
Indicates the specific method or scheme used to discretize continuous values into quantized levels.
- 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_69f0d625b09481909b0b69aea1e846c8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672af46e48190b76e9298e7d23eef |
completed | May 2, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 7:19 p.m.