Triple
T29694144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M2-branes |
E751296
|
entity |
| Predicate | hasTensionScaling |
P167610
|
FINISHED |
| Object | T ∝ 1/l_p^3 |
—
|
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: T ∝ 1/l_p^3 | Statement: [M2-branes, hasTensionScaling, T ∝ 1/l_p^3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTensionScaling Context triple: [M2-branes, hasTensionScaling, T ∝ 1/l_p^3]
-
A.
tensionScaling
chosen
Indicates how the level or intensity of tension changes in proportion to another factor, such as scale, distance, or magnitude.
-
B.
hasTension
Indicates the presence of strain, stress, or conflict between entities in their relationship or interaction.
-
C.
hasTensioningSystem
Indicates that an object is equipped with a mechanism specifically designed to apply, adjust, or maintain tension in another component or system.
-
D.
tensionFactor
Indicates the degree or intensity of tension present in the relationship or interaction between entities.
-
E.
hasTypeOfTension
Indicates that one entity is associated with, or characterized by, a specific kind or category of tension.
- 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_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: April 28, 2026, 7:19 p.m.