Triple
T14497636
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hurricane Mountain |
E359543
|
entity |
| Predicate | fireTowerType |
P114467
|
FINISHED |
| Object | historic fire lookout tower |
—
|
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: historic fire lookout tower | Statement: [Hurricane Mountain, fireTowerType, historic fire lookout tower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireTowerType Context triple: [Hurricane Mountain, fireTowerType, historic fire lookout tower]
-
A.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
B.
fireSupportType
Indicates the specific kind or category of supporting fire (such as artillery, air support, or naval gunfire) being provided in a military context.
-
C.
fireShape
Indicates that one entity has the specified geometric or visual form of a fire or flame.
-
D.
fortType
Indicates the specific kind or classification of a fort associated with an entity.
-
E.
fireModes
Indicates the different ways or settings in which a weapon or device can be fired or operated.
- 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.