Triple
T30312532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 37 |
E770964
|
entity |
| Predicate | nearCitySegment |
P3945
|
FINISHED |
| Object | Interstate 37 near San Antonio |
—
|
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: Interstate 37 near San Antonio | Statement: [Interstate 37, nearCitySegment, Interstate 37 near San Antonio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearCitySegment Context triple: [Interstate 37, nearCitySegment, Interstate 37 near San Antonio]
-
A.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
B.
nearbyUrbanCenter
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
C.
passesNearCity
chosen
Indicates that the path, route, or trajectory of one entity goes close to, but not necessarily through, a specified city.
-
D.
nearByCityState
Indicates that a city is geographically close to or within the same general area as a specified state.
-
E.
hasNearbyCityArea
Indicates that one area is geographically close to or adjacent to a city area.
- 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_69f22488f224819081b0f3ec41ab975c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6816ceb688190b2e5f01205f3c550 |
completed | May 2, 2026, 10:57 p.m. |
| PD | Predicate disambiguation | batch_69f6760216108190bbb708d53a6c2c25 |
completed | May 2, 2026, 10:09 p.m. |
Created at: April 29, 2026, 7:50 p.m.