Triple
T7946863
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chu bamboo slips |
E184518
|
entity |
| Predicate | methodOfInscription |
P79972
|
FINISHED |
| Object | brush and ink |
—
|
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: brush and ink | Statement: [Chu bamboo slips, methodOfInscription, brush and ink]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: methodOfInscription Context triple: [Chu bamboo slips, methodOfInscription, brush and ink]
-
A.
isInscribedOn
Indicates that text, symbols, or markings are written, carved, or otherwise permanently placed onto the surface of an object.
-
B.
materialTypicallyInscribedOn
Indicates the material that is most commonly used as the surface or medium on which something is inscribed.
-
C.
sculptorInscription
Indicates that an inscription identifies the sculptor responsible for creating a particular sculpture or artwork.
-
D.
inscribedOn
Indicates that text, symbols, or markings are written or carved onto the surface of an object.
-
E.
hasNumberOfNamesInscribed
Indicates the quantity of distinct names that are inscribed on a given entity.
- F. None of above. chosen
Provenance (4 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_69ca8291c2008190b1b8832c87814bcf |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3b29a570819091a2ac185a8d57c4 |
completed | March 31, 2026, 3:10 a.m. |
| PD | Predicate disambiguation | batch_69cae93526d081909303265bf60419fd |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf788db1c8190839523e7777961d6 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:09 p.m.