Triple
T5910090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Col |
E131436
|
entity |
| Predicate | typicalCampNumber |
P56116
|
FINISHED |
| Object | Camp I on the north side of Everest |
—
|
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: Camp I on the north side of Everest | Statement: [North Col, typicalCampNumber, Camp I on the north side of Everest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCampNumber Context triple: [North Col, typicalCampNumber, Camp I on the north side of Everest]
-
A.
numberOfCamps
chosen
Indicates the total count of camps associated with or involved in a given entity or situation.
-
B.
typicalCamp1Altitude_m
Indicates the usual or characteristic altitude, in meters, at which the first camp in a sequence of camps is located.
-
C.
typicalCamp3Altitude_m
Indicates the usual elevation, in meters, at which the third camp in a sequence of camps is located.
-
D.
typicalCamp4Altitude_m
Indicates the altitude in meters that is typically associated with a mountain’s Camp 4 location.
-
E.
notableCamp
Indicates that an entity is a camp that is notable or significant in some recognized way (e.g., historically, culturally, or by prominence).
- 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_69c008593a44819081a07ae0efe6c574 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0334fcf6481908e8e74105de9d49b |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 3:59 p.m.