Triple
T12165585
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ahu Akivi |
E289824
|
entity |
| Predicate | hasMoaiWeightRange |
P103038
|
FINISHED |
| Object | around 4 metric tons |
—
|
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: around 4 metric tons | Statement: [Ahu Akivi, hasMoaiWeightRange, around 4 metric tons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoaiWeightRange Context triple: [Ahu Akivi, hasMoaiWeightRange, around 4 metric tons]
-
A.
weightRangeDescription
Indicates the textual description that specifies the range within which an entity’s weight falls.
-
B.
hasMoaiWithPukao
Indicates that something includes or features a moai statue that is specifically topped with a pukao (a stone hat or topknot).
-
C.
numberOfMoai
Indicates the quantity or count of Moai associated with a given subject.
-
D.
typicalMassRange
chosen
Indicates the usual or expected range of mass values associated with an entity.
-
E.
hasMassScale
Indicates that an entity is associated with a particular mass measurement scale or system used to quantify its mass.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91621ca6c81908365732f361aef13 |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150e85348190b9b47cda4a17dcd0 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.