Triple
T6846508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antoshka |
E157907
|
entity |
| Predicate | notTypicallyUsedAs |
P40931
|
FINISHED |
| Object | formal legal name |
—
|
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: formal legal name | Statement: [Antoshka, notTypicallyUsedAs, formal legal name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notTypicallyUsedAs Context triple: [Antoshka, notTypicallyUsedAs, formal legal name]
-
A.
notTypicallyUsedFor
Indicates that something is generally not used for a particular purpose, function, or activity under normal circumstances.
-
B.
notTypically
chosen
Indicates that the referenced situation, behavior, or relationship does not usually or normally occur under standard or expected conditions.
-
C.
notUsedOnModel
Indicates that a particular item, component, or feature is not applied, installed, or utilized on the specified model.
-
D.
notDescribedAs
Indicates that an entity is explicitly not characterized, labeled, or referred to using a particular description or term.
-
E.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
- 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_69c6882ed4c081909dc465a7cf8838be |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d7cbe4488190b41ddf953f12f55f |
completed | March 27, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69c6d09f90648190bc0a462c7d59de1b |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:20 p.m.