Triple
T31792267
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | structural operational semantics |
E811501
|
entity |
| Predicate | oftenRepresentsStateAs |
P115778
|
FINISHED |
| Object | store |
—
|
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: store | Statement: [structural operational semantics, oftenRepresentsStateAs, store]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenRepresentsStateAs Context triple: [structural operational semantics, oftenRepresentsStateAs, store]
-
A.
representsStateIn
chosen
Indicates that one entity serves as a representative or embodiment of a particular state, condition, or status of another entity.
-
B.
representsStateWith
Indicates that an entity is associated with or characterized by a particular state or condition.
-
C.
stateRepresentation
Indicates that one entity serves as a depiction, model, or encoding of the condition, configuration, or status of another entity.
-
D.
regardsTheStateAs
Indicates viewing or treating the state in a particular way, typically expressing an attitude, judgment, or evaluative stance toward it.
-
E.
portraysState
Indicates that one entity visually or symbolically represents or depicts the condition, status, or situation of another entity.
- 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fb2e940d5c8190bceae77daf4ef512 |
completed | May 6, 2026, 12:05 p.m. |
| PD | Predicate disambiguation | batch_69f9fec70bd881909c658a3c5020318b |
completed | May 5, 2026, 2:29 p.m. |
Created at: April 30, 2026, 11:39 p.m.