Triple
T32793879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 302 in Maine |
E838704
|
entity |
| Predicate | hasAlternateNameInSection |
P627
|
FINISHED |
| Object | Roosevelt Trail |
—
|
NE NERFINISHED |
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: Roosevelt Trail | Statement: [U.S. Route 302 in Maine, hasAlternateNameInSection, Roosevelt Trail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlternateNameInSection Context triple: [U.S. Route 302 in Maine, hasAlternateNameInSection, Roosevelt Trail]
-
A.
hasSectionKnownAs
chosen
Indicates that an entity includes a section or part that is referred to by a specific name.
-
B.
hasTitleHolderAlternativeName
Indicates that an entity serving as a title holder is known by an alternative or additional name.
-
C.
haveAlternativeTitle
Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
-
D.
hasAlternativeTitleCombination
Indicates that an entity is associated with one or more alternative titles considered together as a specific combination or set.
-
E.
hasAlternateKeySections
Indicates that an entity is associated with one or more alternative key segments or components that can also uniquely identify it.
- 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_69f3493c7f6881908edf2aa13631d1e0 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: May 1, 2026, 1:14 a.m.