Triple
T14497634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Mountain |
E359543
|
entity |
| Predicate | fireTowerUse |
P114465
|
FINISHED |
| Object | observation tower for visitors |
—
|
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: observation tower for visitors | Statement: [Hurricane Mountain, fireTowerUse, observation tower for visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireTowerUse Context triple: [Hurricane Mountain, fireTowerUse, observation tower for visitors]
-
A.
fireUse
Indicates the use or application of fire by one entity on, with, or for another entity or object.
-
B.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
C.
fireShape
Indicates that one entity has the specified geometric or visual form of a fire or flame.
-
D.
fireEffect
Indicates that one entity produces, causes, or is associated with a fire-related impact or consequence on another entity.
-
E.
fireServiceBy
Indicates that a fire protection or firefighting service is provided, operated, or carried out by a specified agent or organization.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9311cc748190880c784f173b7f2b |
completed | April 14, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69de5c4ccba08190a988bfda0bc9f5cb |
completed | April 14, 2026, 3:25 p.m. |
| PDg | Predicate description generation | batch_69de5fb4de14819092acdecbd201d672 |
completed | April 14, 2026, 3:39 p.m. |
Created at: April 10, 2026, 1:21 a.m.