Triple
T7416110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Silverdome |
E171133
|
entity |
| Predicate | distanceFromDetroit |
P25679
|
FINISHED |
| Object | approximately 30 miles north of downtown Detroit |
—
|
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: approximately 30 miles north of downtown Detroit | Statement: [Silverdome, distanceFromDetroit, approximately 30 miles north of downtown Detroit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromDetroit Context triple: [Silverdome, distanceFromDetroit, approximately 30 miles north of downtown Detroit]
-
A.
distanceToDetroit
chosen
Indicates the measured or calculated spatial distance between a given entity and the location of Detroit.
-
B.
distanceToMadison
Indicates the spatial distance between a given entity and the location identified as Madison.
-
C.
distanceToMilwaukee
Indicates the measured or calculated spatial distance between a given entity’s location and the city of Milwaukee.
-
D.
distanceFromTacoma (miles)
Indicates the physical distance, measured in miles, between an entity’s location and the city of Tacoma.
-
E.
distanceFromLosAngeles
Indicates the measured or specified distance between a given entity’s location and the city of Los Angeles.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2c643248190a387abba2f482b25 |
completed | March 27, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.