Triple
T12619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Whitney |
E254
|
entity |
| Predicate | firstAscent |
P1320
|
FINISHED |
| Object | 1873 |
—
|
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: 1873 | Statement: [Mount Whitney, firstAscent, 1873]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstAscent Context triple: [Mount Whitney, firstAscent, 1873]
-
A.
highestPoint
Indicates that one entity is the point with the greatest elevation or height relative to another entity or defined area.
-
B.
elevation
Indicates the vertical height or altitude of one entity relative to a reference level or another entity.
-
C.
firstAwarded
Indicates the time or occasion when an award, honor, or recognition was given for the very first time.
-
D.
lowestPoint
Indicates that one entity is the point with the minimum vertical position or value relative to another entity or within a specified context.
-
E.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
- F. None of above. chosen
Provenance (4 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a243abb2ec8190937365e5ecec52ad |
completed | Feb. 28, 2026, 1:23 a.m. |
| PD | Predicate disambiguation | batch_69a23fe9470c8190918a6ca1df168646 |
completed | Feb. 28, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69a243aa85848190813154e8a6495200 |
completed | Feb. 28, 2026, 1:23 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.