Triple
T28338157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shaolin Rou Quan |
E717735
|
entity |
| Predicate | sharesSimilarityWith |
P94757
|
FINISHED |
| Object | Taijiquan |
—
|
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: Taijiquan | Statement: [Shaolin Rou Quan, sharesSimilarityWith, Taijiquan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesSimilarityWith Context triple: [Shaolin Rou Quan, sharesSimilarityWith, Taijiquan]
-
A.
sharesAlignmentWith
Indicates that two entities have the same or sufficiently similar alignment, orientation, or stance according to a defined alignment system.
-
B.
hasSimilarityTo
chosen
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
C.
moreSimilarTo
Indicates that one entity bears a greater degree of similarity to a second entity than to a third entity, according to some defined similarity measure.
-
D.
sharesGivenNameWith
Indicates that two entities have the same given (first) name.
-
E.
sharesCharacterWith
Indicates that two entities have at least one character (such as a letter, symbol, or glyph) in common.
- 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_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69fd44474ed48190ac372e4c88d762ed |
completed | May 8, 2026, 2:02 a.m. |
| PD | Predicate disambiguation | batch_69fd41ef28a48190a66959be5c964461 |
completed | May 8, 2026, 1:52 a.m. |
Created at: April 28, 2026, 12:37 a.m.