Triple
T29626999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Squadron |
E755170
|
entity |
| Predicate | parallelFormation |
P150562
|
FINISHED |
| Object | Red Squadron |
—
|
NE NERFINISHED |
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: Red Squadron | Statement: [White Squadron, parallelFormation, Red Squadron]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: parallelFormation Context triple: [White Squadron, parallelFormation, Red Squadron]
-
A.
parallel
Indicates that two or more entities maintain a constant separation and direction without intersecting or converging.
-
B.
parallelType
chosen
Indicates that one entity runs in parallel to another, specifying the type or manner of their parallel relationship.
-
C.
parallelPassage
Indicates that one text segment corresponds closely in content or structure to another, such that they can be considered parallel versions or accounts of the same material.
-
D.
parallelSeeTo
Indicates that one entity observes or attends to another entity in a manner that is simultaneous or coordinated with a comparable act of seeing by a different entity.
-
E.
onFormation
Indicates that one entity is located on or attached to the surface of a formation (such as a geological or structural feature).
- 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_69f0ef86b6ec8190a87fff07fd983b1e |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f67d3624248190a36a9b2d2e9778d4 |
completed | May 2, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 6:38 p.m.