Triple
T37736695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xuetou Chongxian’s one-hundred koan collection |
E940295
|
entity |
| Predicate | coreMaterialFor |
P131547
|
FINISHED |
| Object | Blue Cliff Record |
—
|
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: Blue Cliff Record | Statement: [Xuetou Chongxian’s one-hundred koan collection, coreMaterialFor, Blue Cliff Record]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coreMaterialFor Context triple: [Xuetou Chongxian’s one-hundred koan collection, coreMaterialFor, Blue Cliff Record]
-
A.
featuresMaterialFrom
Indicates that one entity incorporates, contains, or is composed of material originating from another entity.
-
B.
originalMaterialFor
chosen
Indicates that one entity serves as the source or basis material from which another entity is derived, adapted, or created.
-
C.
featuresMaterialType
Indicates that an entity is characterized by or incorporates a specific type of material.
-
D.
testedMaterial
Indicates that an entity has been used as the material or substance on which a test or experiment was performed.
-
E.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
- 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_69f76edefd048190a32212c5c3919531 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaef0cec881908c2742d77d145901 |
completed | May 6, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.