Triple
T11182974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annetta, Texas |
E264587
|
entity |
| Predicate | county |
P75
|
FINISHED |
| Object | Parker County |
E1242848
|
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: Parker County | Statement: [Annetta, Texas, county, Parker County]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Parker County Context triple: [Annetta, Texas, county, Parker County]
-
A.
Parker County
chosen
Parker County is a county in north-central Texas that includes communities such as Hudson Oaks and is part of the Dallas–Fort Worth metropolitan area.
-
B.
Hunt County
Hunt County is a county in northeastern Texas that includes both rural communities and the city of Greenville as its county seat.
-
C.
Gregg County
Gregg County is a county in East Texas best known for its county seat, Longview, and its role in the region’s oil and gas industry.
-
D.
Gray County
Gray County is a rural county in the Texas Panhandle best known for its oil industry and county seat, Pampa.
-
E.
Burnet County
Burnet County is a central Texas county known for its scenic lakes, rolling hills, and outdoor recreation in the Texas Hill Country.
- 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_69d6aa9dafac8190bd90d2c74f661aa7 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8a9c5e081908c85b41a268428fb |
completed | April 9, 2026, 5:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a011b2fc8f88190b9bd2887149e3d68 |
completed | May 10, 2026, 11:56 p.m. |
Created at: April 8, 2026, 9:29 p.m.