Triple
T6000787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | God Bless America |
E133588
|
entity |
| Predicate | mentionsGeographicFeature |
P53641
|
FINISHED |
| Object | mountains |
—
|
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: mountains | Statement: [God Bless America, mentionsGeographicFeature, mountains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mentionsGeographicFeature Context triple: [God Bless America, mentionsGeographicFeature, mountains]
-
A.
refersToGeographicFeature
chosen
Indicates that one entity makes reference to, denotes, or is associated with a specific geographic feature such as a landform, body of water, or other physical location.
-
B.
locatedInGeographicFeature
Indicates that something is situated within or on a specific natural geographic feature (such as a mountain, river, valley, or lake).
-
C.
isGeographicalEntity
Indicates that something exists as a distinct geographic feature, area, or place within physical space.
-
D.
hasGeographyCharacteristic
Indicates that an entity possesses a specific geographical feature, property, or attribute.
-
E.
impliesGeographicalFact
Indicates that one geographical statement or condition logically entails the truth of another geographical fact.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04ee7c0e08190a6e78969448b070a |
completed | March 22, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c049e152e88190979ab80cb9b50321 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:05 p.m.