Triple
T4874125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauna Kea |
E109158
|
entity |
| Predicate | hasLandUseControversy |
P1783
|
FINISHED |
| Object | telescope construction |
—
|
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: telescope construction | Statement: [Mauna Kea, hasLandUseControversy, telescope construction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandUseControversy Context triple: [Mauna Kea, hasLandUseControversy, telescope construction]
-
A.
locationOfControversy
Indicates the place or setting where a dispute, debate, or controversy occurs or is centered.
-
B.
controversialBecause
Indicates that one entity is considered controversial specifically due to, or as a result of, its relationship with or association to another entity.
-
C.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
D.
controversyType
Indicates the specific kind or category of controversy associated with an entity or situation.
-
E.
controversy
chosen
Indicates a situation in which there is active disagreement, dispute, or public debate between parties over a particular issue, action, or claim.
- 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_69bd440d96a48190b0c87069adef2af1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c28e56081908ee411ac94c3769e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:27 p.m.