Triple
T12097795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moai statues |
E288114
|
entity |
| Predicate | tallestStandingMoaiHeight |
P1724
|
FINISHED |
| Object | about 10 metres |
—
|
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 10 metres | Statement: [Moai statues, tallestStandingMoaiHeight, about 10 metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tallestStandingMoaiHeight Context triple: [Moai statues, tallestStandingMoaiHeight, about 10 metres]
-
A.
statueHeight
chosen
Indicates the height measurement of a statue in some specified unit.
-
B.
approximateNumberOfMoai
Indicates that one entity specifies an estimated or approximate count of Moai associated with another entity.
-
C.
highestPillarApproximateHeight
Indicates the estimated height value of the tallest pillar in a given context or structure.
-
D.
heightRangeOfStelae
Indicates the span between the minimum and maximum heights of the stelae involved.
-
E.
rankByHeightWorld
Indicates an ordering of entities based on their relative height compared to all others in the world.
- 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.