Triple
T12097799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moai statues |
E288114
|
entity |
| Predicate | largestUnfinishedMoaiWeight |
P57708
|
FINISHED |
| Object | about 270 tonnes |
—
|
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 270 tonnes | Statement: [Moai statues, largestUnfinishedMoaiWeight, about 270 tonnes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestUnfinishedMoaiWeight Context triple: [Moai statues, largestUnfinishedMoaiWeight, about 270 tonnes]
-
A.
approximateNumberOfMoai
Indicates that one entity specifies an estimated or approximate count of Moai associated with another entity.
-
B.
maximumRecordedMass
chosen
Indicates the greatest mass value that has been observed and recorded for an entity within a given context.
-
C.
numberOfMoai
Indicates the quantity or count of Moai associated with a given subject.
-
D.
hasMoaiWithPukao
Indicates that something includes or features a moai statue that is specifically topped with a pukao (a stone hat or topknot).
-
E.
largestFigureLengthApprox
Indicates an approximate measurement of the length of the largest figure involved in the relationship or context.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.