Triple
T9889606
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banliang coin |
E181419
|
entity |
| Predicate | meaningOfInscription |
P11402
|
FINISHED |
| Object | half liang |
—
|
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: half liang | Statement: [Banliang coin, meaningOfInscription, half liang]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningOfInscription Context triple: [Banliang coin, meaningOfInscription, half liang]
-
A.
reverseInscriptionMeaning
Indicates that the inscription’s meaning is the reverse or opposite of the usual or expected interpretation.
-
B.
inscriptionMeaning
chosen
Indicates that an inscription conveys a particular meaning, message, or content.
-
C.
materialTypicallyInscribedOn
Indicates the material that is most commonly used as the surface or medium on which something is inscribed.
-
D.
scriptOfInscription
Indicates the writing system or script in which a given inscription is written.
-
E.
mainContentOfInscriptions
Indicates that something represents the primary textual or symbolic content conveyed by a set of inscriptions.
- 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_69ca8283a6708190801af7a25a7ebb9f |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cdb47be2988190811a99dc56ae542a |
completed | April 2, 2026, 12:12 a.m. |
| PD | Predicate disambiguation | batch_69cd1d810ed48190a252b70e9390c8f3 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:39 p.m.