Triple
T14070418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jakhu Hill |
E338590
|
entity |
| Predicate | hasStatueHeightApprox |
P1724
|
FINISHED |
| Object | about 33 metres for the Hanuman statue |
—
|
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 33 metres for the Hanuman statue | Statement: [Jakhu Hill, hasStatueHeightApprox, about 33 metres for the Hanuman statue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStatueHeightApprox Context triple: [Jakhu Hill, hasStatueHeightApprox, about 33 metres for the Hanuman statue]
-
A.
statueHeight
chosen
Indicates the height measurement of a statue in some specified unit.
-
B.
hasStatue
Indicates that one entity possesses, contains, or is associated with a statue representing or located within it.
-
C.
statueWeight
Indicates that a statue has a specific weight or mass.
-
D.
heightEstimate
Indicates an estimated or approximate value for the height of an entity, rather than a precisely measured height.
-
E.
hasTowerHeight
Indicates that an entity (such as a tower or structure) has a specific height value associated with it.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de568d0404819087e0fe37c72162cb |
completed | April 14, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.