Triple
T34752286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sibe script |
E1001814
|
entity |
| Predicate | hasDistinctivenessFrom |
P18160
|
FINISHED |
| Object | classical Manchu orthography |
—
|
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: classical Manchu orthography | Statement: [Sibe script, hasDistinctivenessFrom, classical Manchu orthography]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDistinctivenessFrom Context triple: [Sibe script, hasDistinctivenessFrom, classical Manchu orthography]
-
A.
isDistinctiveGivenNameOf
Indicates that a given name uniquely and distinctively identifies or characterizes a particular entity compared to others.
-
B.
hasDistinctFeature
chosen
Indicates that an entity possesses a specific characteristic or attribute that differentiates it from others.
-
C.
hasDistinctiveShape
Indicates that an entity possesses a shape or form that is notably different from others and can be easily recognized or distinguished.
-
D.
distinguishingTrait
Indicates that a particular characteristic or feature uniquely differentiates one entity from another.
-
E.
hasDistinctLettersFor
Indicates that one entity is associated with another such that the letters used in the first are all different from (i.e., share no letters with) those used in the second.
- 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_69f76db0fb30819096709d43f9a1f45f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff21cbd9108190a52c0ba42004c669 |
completed | May 9, 2026, noon |
| PD | Predicate disambiguation | batch_69ff1faea91881908c626c70bca5100a |
completed | May 9, 2026, 11:51 a.m. |
Created at: May 3, 2026, 3:59 p.m.