Triple
T9663128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cretan hieroglyphs |
E233635
|
entity |
| Predicate | hasApproximateNumberOfSigns |
P68470
|
FINISHED |
| Object | about 90 signs |
—
|
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: about 90 signs | Statement: [Cretan hieroglyphs, hasApproximateNumberOfSigns, about 90 signs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateNumberOfSigns Context triple: [Cretan hieroglyphs, hasApproximateNumberOfSigns, about 90 signs]
-
A.
numberOfSigns
Indicates the quantity of signs associated with or present in relation to a given entity or context.
-
B.
hasApproximateNumberOfLetters
Indicates that an entity is associated with a number that roughly, but not exactly, corresponds to the count of letters it contains.
-
C.
numberOfSyllabicSignsApprox
Indicates an approximate count of syllabic signs associated with an entity.
-
D.
hasApproximateNumberOfAttestedWords
Indicates that an entity is associated with an estimated or approximate count of words that are documented or attested for it.
-
E.
hasApproximateNumberOfPictographs
chosen
Indicates that an entity is associated with a quantity of pictographs that is not exact but estimated or approximate.
- 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_69ca848d3b6c8190ae98ea554dea58df |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c0cde048190b5a8e1548825d4d9 |
completed | April 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b3239c8190b3ae3b9bd121e4bd |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:14 p.m.