Triple
T19807152
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elmore County, Alabama |
E475842
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Elmore, Alabama
Elmore, Alabama is a small town in central Alabama that forms part of the Montgomery metropolitan area.
|
E1468871
|
NE FINISHED |
How this triple was built (4 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: Elmore, Alabama | Statement: [Elmore County, Alabama, contains, Elmore, Alabama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elmore, Alabama Context triple: [Elmore County, Alabama, contains, Elmore, Alabama]
-
A.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
-
B.
Newton, Alabama
Newton, Alabama is a small town in southeastern Alabama known for its rural character and location within the Dothan metropolitan area.
-
C.
Moody, Alabama
Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
-
D.
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.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Elmore, Alabama Triple: [Elmore County, Alabama, contains, Elmore, Alabama]
Generated description
Elmore, Alabama is a small town in central Alabama that forms part of the Montgomery metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Elmore, Alabama Target entity description: Elmore, Alabama is a small town in central Alabama that forms part of the Montgomery metropolitan area.
-
A.
Steele, Alabama
Steele, Alabama is a small town in northeastern Alabama known for its rural character and location within St. Clair County.
-
B.
Newton, Alabama
Newton, Alabama is a small town in southeastern Alabama known for its rural character and location within the Dothan metropolitan area.
-
C.
Moody, Alabama
Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
-
D.
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.
-
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. chosen
Provenance (5 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_69d8e51bc4208190a1c57d8c5d1b15e4 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65428f5c48190be6ae0d6a77675d2 |
completed | April 20, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a096da3b8e88190bae1daccb216d35a |
completed | May 17, 2026, 7:26 a.m. |
| NEDg | Description generation | batch_6a096e80955c819080873bc728d9ab5d |
completed | May 17, 2026, 7:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a096f5e96cc8190b3be5a773868bd32 |
completed | May 17, 2026, 7:33 a.m. |
Created at: April 10, 2026, 1:49 p.m.