Triple
T12285397
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rongorongo tablets |
E292815
|
entity |
| Predicate | glyphCount |
P4428
|
FINISHED |
| Object | hundreds of distinct 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: hundreds of distinct signs | Statement: [Rongorongo tablets, glyphCount, hundreds of distinct signs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: glyphCount Context triple: [Rongorongo tablets, glyphCount, hundreds of distinct signs]
-
A.
hasGlyphRepertoireSize
chosen
Indicates the number of distinct glyphs included in an entity’s glyph repertoire.
-
B.
graphicCharactersCount
Indicates the number of printable (non-control) characters present in a given text or string.
-
C.
hasGlyphsFor
Indicates that one entity provides or contains the necessary glyphs or visual symbols to represent another entity.
-
D.
characterSetSize
Indicates the total number of distinct characters contained in or allowed by a given character set.
-
E.
hasApproximateNumberOfPictographs
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_69d6ab690ad081908c0ed3870ec82d53 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d9261e1570819084bb4fdb44aa6aea |
completed | April 10, 2026, 4:32 p.m. |
| PD | Predicate disambiguation | batch_69d91c4d9a9c8190aeb7beaf9792d8f0 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:52 p.m.