Triple
T20155972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Candler County |
E491566
|
entity |
| Predicate | hasCountySeat |
P383
|
FINISHED |
| Object |
Metter
Metter is a small city in southeastern Georgia, United States, known as the principal community and administrative center of Candler County.
|
E1414822
|
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: Metter | Statement: [Candler County, hasCountySeat, Metter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Metter Context triple: [Candler County, hasCountySeat, Metter]
-
A.
Metter
The Metter is a river in Germany that flows through the state of Baden-Württemberg and ultimately joins the Enz River.
-
B.
Mettet
Mettet is a municipality in Wallonia, Belgium, known for its rural character and the Circuit Jules Tacheny motor racing track.
-
C.
Metzad
Metzad is an Israeli settlement in the Gush Etzion region of the West Bank, known as a small religious community established after 1967.
-
D.
Mest
Mest is an American pop punk band known for its catchy melodies, energetic style, and early-2000s presence on the punk rock scene.
-
E.
Mette
Mette is a given name most notably associated with American dancer and actress Mette Towley, known for her work in music videos and film.
- 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: Metter Triple: [Candler County, hasCountySeat, Metter]
Generated description
Metter is a small city in southeastern Georgia, United States, known as the principal community and administrative center of Candler County.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Metter Target entity description: Metter is a small city in southeastern Georgia, United States, known as the principal community and administrative center of Candler County.
-
A.
Metter
The Metter is a river in Germany that flows through the state of Baden-Württemberg and ultimately joins the Enz River.
-
B.
Mettet
Mettet is a municipality in Wallonia, Belgium, known for its rural character and the Circuit Jules Tacheny motor racing track.
-
C.
Metzad
Metzad is an Israeli settlement in the Gush Etzion region of the West Bank, known as a small religious community established after 1967.
-
D.
Mest
Mest is an American pop punk band known for its catchy melodies, energetic style, and early-2000s presence on the punk rock scene.
-
E.
Mette
Mette is a given name most notably associated with American dancer and actress Mette Towley, known for her work in music videos and film.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e667e0a0488190a25d92aaf300be4a |
completed | April 20, 2026, 5:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a083476e2d08190807674e3f61382bc |
completed | May 16, 2026, 9:10 a.m. |
| NEDg | Description generation | batch_6a08351511888190a144ff037abdddfb |
completed | May 16, 2026, 9:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0835e4248c8190817907ca46cd5cff |
completed | May 16, 2026, 9:16 a.m. |
Created at: April 11, 2026, 11:34 p.m.