Triple
T26991901
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ConcreteState |
E679879
|
entity |
| Predicate | oftenNamedAs |
P71235
|
FINISHED |
| Object | ConcreteStateA |
—
|
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: ConcreteStateA | Statement: [ConcreteState, oftenNamedAs, ConcreteStateA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenNamedAs Context triple: [ConcreteState, oftenNamedAs, ConcreteStateA]
-
A.
oftenNamedAfter
Indicates that one entity frequently receives its name from or in honor of another entity.
-
B.
oftenUsedAsNameFor
chosen
Indicates that something frequently serves as a name or designation for another entity.
-
C.
knownAsBy
Indicates that one entity is referred to or recognized by another entity using a particular name or designation.
-
D.
oftenRenamedAs
Indicates that an entity is frequently given a different name or title, reflecting common renaming or rebranding over time or across contexts.
-
E.
namedAccordingTo
Indicates that one entity is given a name that follows, references, or is derived from another entity or source.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 6:52 a.m.