Triple
T38659104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saser Kangri II |
E939978
|
entity |
| Predicate | rankByHeightInIndia |
P177332
|
FINISHED |
| Object | among the highest peaks in India |
—
|
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: among the highest peaks in India | Statement: [Saser Kangri II, rankByHeightInIndia, among the highest peaks in India]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankByHeightInIndia Context triple: [Saser Kangri II, rankByHeightInIndia, among the highest peaks in India]
-
A.
rankingByHeightInIndia
chosen
Indicates the relative ordering of entities based on their height specifically within the context of India.
-
B.
rankWithinIndia
Indicates the position or standing of something in comparison to others specifically within the context of India.
-
C.
rankByHeightInMaharashtra
Indicates the relative ordering of entities based on their height within the geographic region of Maharashtra.
-
D.
rankByLengthInIndia
Indicates an ordering of items based on their length specifically within the context or boundaries of India.
-
E.
rankByPopulationInIndia
Indicates the relative ordering of entities based on their population size within India.
- 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_69f76ede49648190a48bfe47032a05a3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcdfbc71c481908ba7f87907b17782 |
completed | May 7, 2026, 6:53 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe580b8819087f143596b2c79c0 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:33 p.m.