Triple
T29734350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type IIA string theory |
E752413
|
entity |
| Predicate | hasStringCoupling |
P31186
|
FINISHED |
| Object | gs |
—
|
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: gs | Statement: [Type IIA string theory, hasStringCoupling, gs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStringCoupling Context triple: [Type IIA string theory, hasStringCoupling, gs]
-
A.
hasCoupling
Indicates that two entities are linked or joined together in a way that allows them to interact, transfer, or coordinate motion, energy, or information.
-
B.
hasStrings
Indicates that an entity possesses or is associated with one or more strings (such as string-like components, text values, or string elements).
-
C.
hasCouplingConstant
chosen
Indicates that one entity is associated with a specific coupling constant value that quantifies the strength of an interaction or relationship.
-
D.
hasStringParts
Indicates that a whole string is composed of, or can be decomposed into, one or more constituent string segments or parts.
-
E.
hasStringType
Indicates that an entity is associated with, defined by, or constrained to a specific string data type.
- 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_69f0d62a36a88190bf860f00da433ff8 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
Created at: April 28, 2026, 7:44 p.m.