Triple
T22290695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AL-06 |
E550985
|
entity |
| Predicate | includesCity |
P3207
|
FINISHED |
| Object | Alabaster, Alabama |
—
|
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: Alabaster, Alabama | Statement: [AL-06, includesCity, Alabaster, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alabaster, Alabama Context triple: [AL-06, includesCity, Alabaster, Alabama]
-
A.
Alabaster, Alabama
chosen
Alabaster, Alabama is a rapidly growing suburban city in central Alabama known for its residential communities, schools, and retail centers just south of Birmingham.
-
B.
Elmore, Alabama
Elmore, Alabama is a small town in central Alabama that forms part of the Montgomery metropolitan area.
-
C.
Sylvania, Alabama
Sylvania, Alabama is a small rural town in northeastern Alabama known for its close-knit community and location atop Sand Mountain.
-
D.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
-
E.
Ensley, Alabama
Ensley, Alabama is a historic industrial neighborhood in Birmingham that developed as a major steelmaking and manufacturing center in the late 19th and early 20th centuries.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1560c47e481908b33de63a11e25de |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 16, 2026, 8:41 p.m.