Triple
T30182075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leonidas 1 |
E767227
|
entity |
| Predicate | productionVariantNumber |
P64697
|
FINISHED |
| Object | early production model |
—
|
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: early production model | Statement: [Leonidas 1, productionVariantNumber, early production model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: productionVariantNumber Context triple: [Leonidas 1, productionVariantNumber, early production model]
-
A.
isNumberedVariantOf
Indicates that one entity is a specific numbered version or edition of another, more general entity.
-
B.
productVariant
chosen
Indicates that one entity is a specific variant or version of a more general product entity.
-
C.
workNumberingVariant
Indicates that one work serves as an alternative or variant numbering representation of another work within a numbering or cataloging system.
-
D.
parameterizedVariant
Indicates that one entity is a specific parameterized form or configuration variant derived from another base entity.
-
E.
modelNumber
Indicates that one entity is the specific model identifier or code assigned to another entity (such as a product or device).
- 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_69f2247cc3d88190811dec3face94bf5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 29, 2026, 7:26 p.m.