Triple
T13025323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bacliff, Texas |
E326288
|
entity |
| Predicate | distanceToHoustonDowntown |
P1299
|
FINISHED |
| Object | approximately 35 miles southeast |
—
|
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 35 miles southeast | Statement: [Bacliff, Texas, distanceToHoustonDowntown, approximately 35 miles southeast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToHoustonDowntown Context triple: [Bacliff, Texas, distanceToHoustonDowntown, approximately 35 miles southeast]
-
A.
distanceFromDallas
Indicates the measured distance between a given place or entity and the city of Dallas.
-
B.
distanceToAustin
Indicates the spatial distance between a given entity or location and the city of Austin.
-
C.
distanceFromSanAntonio
Indicates the measured or specified distance between an entity and the location of San Antonio.
-
D.
distanceToMcKinney
Indicates the measured or calculated distance between a given entity and the location named McKinney.
-
E.
distanceFromDowntown
chosen
Indicates the physical distance between a given location and the central downtown 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97efac71881908a21d70c3c6ce099 |
completed | April 10, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69d97dc39a0881908119c62e31bf6182 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:53 p.m.