Triple
T9051773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mon language |
E216899
|
entity |
| Predicate | hasAncientCorpus |
P65791
|
FINISHED |
| Object | inscriptions |
—
|
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: inscriptions | Statement: [Mon language, hasAncientCorpus, inscriptions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAncientCorpus Context triple: [Mon language, hasAncientCorpus, inscriptions]
-
A.
isAncient
Indicates that the entity existed or originated in a very distant past, typically far earlier than the commonly referenced historical period.
-
B.
hasEarliestMajorCorpus
Indicates that one entity is associated with the earliest significant or primary body of work (major corpus) relative to other comparable entities.
-
C.
hasNotableCorpus
chosen
Indicates that an entity possesses a significant, well-recognized body of work, texts, or collected materials associated with it.
-
D.
hasHistoricalText
Indicates that an entity is associated with a historical written document or record describing it or its past.
-
E.
hasPartOfCorpus
Indicates that one entity constitutes a component or segment of the overall corpus associated with another entity.
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a700de48190aa9f61d850e01cbd |
completed | April 1, 2026, 1:52 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee566b081909e3cdaf551dbd0ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:10 p.m.