Triple
T2265721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | College Street (New Haven) |
E50139
|
entity |
| Predicate | isDowntownConnector |
P26184
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [College Street (New Haven), isDowntownConnector, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isDowntownConnector Context triple: [College Street (New Haven), isDowntownConnector, true]
-
A.
isDowntownEndpointOf
Indicates that a location serves as the downtown terminus or endpoint of a route, line, or path.
-
B.
connectsDowntownTo
chosen
Indicates a relationship where one location, route, or service provides a direct connection or access to a downtown area.
-
C.
isDowntownCoreOf
Indicates that a location constitutes the central, most urbanized and commercially dense area of a larger city or metropolitan region.
-
D.
hasDowntown
Indicates that a place or city possesses a central downtown area.
-
E.
connectsToHighway
Indicates that one location, road, or route has a direct access point or linkage to a highway.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc2ea65288190bc8644a07a11dfa9 |
completed | March 7, 2026, 6:17 a.m. |
| PD | Predicate disambiguation | batch_69abbdb592588190ac1ef5e8c54575b1 |
completed | March 7, 2026, 5:55 a.m. |
Created at: March 4, 2026, 7:48 p.m.