Triple
T32391881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eagle Pass Port of Entry |
E827693
|
entity |
| Predicate | adjacentCityInUnitedStates |
P66684
|
FINISHED |
| Object | Eagle Pass, Texas |
—
|
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: Eagle Pass, Texas | Statement: [Eagle Pass Port of Entry, adjacentCityInUnitedStates, Eagle Pass, Texas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentCityInUnitedStates Context triple: [Eagle Pass Port of Entry, adjacentCityInUnitedStates, Eagle Pass, Texas]
-
A.
adjacentMajorCity
Indicates that one major city is geographically next to or directly bordering another major city.
-
B.
adjacentCityNorth
Indicates that one city is directly to the north of another city and shares a common boundary or is immediately neighboring it in that direction.
-
C.
adjacentCitySouth
Indicates that one city is directly to the south of another city, sharing a common boundary or being immediately neighboring in that direction.
-
D.
hasNearbyUSCity
chosen
Indicates that one location has at least one city in the United States situated within a specified nearby distance.
-
E.
adjacentProvince
Indicates that two provinces share a common boundary and are directly next to each other geographically.
- 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_69f349184e7481909c6c54428cb9cf12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f791cc969c8190bf187d6031a030d5 |
completed | May 3, 2026, 6:19 p.m. |
| PD | Predicate disambiguation | batch_69f791033d288190b118029fe412b9c9 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 1, 2026, 12:52 a.m.