Triple
T14131999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tahquitz Peak |
E350190
|
entity |
| Predicate | fireLookoutStatus |
P112932
|
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: [Tahquitz Peak, fireLookoutStatus, historic fire lookout tower]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fireLookoutStatus Context triple: [Tahquitz Peak, fireLookoutStatus, historic fire lookout tower]
-
A.
lighthouseStatus
Indicates the operational condition or state (e.g., active, inactive, under maintenance) of a lighthouse at a given time.
-
B.
nearbyWildfire
Indicates that a wildfire is occurring close enough to a given location or entity to be considered in its immediate vicinity.
-
C.
fireOccurred
Indicates that a fire event took place at a specific time and/or location.
-
D.
fireType
Indicates that one entity has a specific classification or category related to fire (e.g., type, kind, or nature of fire).
-
E.
hasLookout
Indicates that one entity serves as a lookout or watchful observer for another entity, monitoring for potential events, threats, or changes.
- 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de610cece88190b4a86500677e5938 |
completed | April 14, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69de05b5e7a08190a16be9ad8b92b80c |
completed | April 14, 2026, 9:15 a.m. |
| PDg | Predicate description generation | batch_69de2398856c81908bed6070e4ca6ab1 |
completed | April 14, 2026, 11:23 a.m. |
Created at: April 9, 2026, 11:16 p.m.