Triple
T29694121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type I string theory |
E751295
|
entity |
| Predicate | stringTypes |
P167801
|
FINISHED |
| Object | open |
—
|
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: open | Statement: [Type I string theory, stringTypes, open]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stringTypes Context triple: [Type I string theory, stringTypes, open]
-
A.
primaryStringTypeFor
Indicates that one entity serves as the main or default string type associated with another entity.
-
B.
textType
Indicates the classification of a text according to its type, format, or genre.
-
C.
linguisticType
Indicates the type or category of language or linguistic system associated with an entity (e.g., spoken, signed, written, or other linguistic modality).
-
D.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
E.
slotType
Indicates the classification or category assigned to a particular slot or position within a structure, system, or sequence.
- 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_69f672af46e48190b76e9298e7d23eef |
completed | May 2, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69f66ac1a4fc81909740d2e52fbe6970 |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66c59de9881909ebbb7b0ae7ab495 |
completed | May 2, 2026, 9:27 p.m. |
Created at: April 28, 2026, 7:19 p.m.