Triple
T7535521
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson County, Alabama |
E178139
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Tarrant, Alabama |
E168426
|
NE 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: Tarrant, Alabama | Statement: [Jefferson County, Alabama, contains, Tarrant, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tarrant, Alabama Context triple: [Jefferson County, Alabama, contains, Tarrant, Alabama]
-
A.
Tarrant, Alabama
chosen
Tarrant, Alabama is a small industrial city in Jefferson County, near Birmingham, known historically for its steel and manufacturing operations.
-
B.
Townley, Alabama
Townley, Alabama is a small unincorporated community located in Walker County in the north-central part of the state.
-
C.
Eldridge, Alabama
Eldridge, Alabama is a small rural town located in Walker County in the northwestern part of the state.
-
D.
Ragland, Alabama
Ragland, Alabama is a small town in central Alabama known for its rural character and location within the Birmingham–Hoover metropolitan area.
-
E.
Sylvania, Alabama
Sylvania, Alabama is a small rural town in northeastern Alabama known for its close-knit community and location atop Sand Mountain.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c69f2acdbc8190b5a8320168c1d0ba |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f84c13208190971096a0b81b0ff2 |
completed | March 27, 2026, 9:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9765b3c5081908c3114271b5d3e15 |
completed | March 29, 2026, 6:58 p.m. |
Created at: March 27, 2026, 3:47 p.m.