Triple
T4536395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamilton County, Tennessee |
E107417
|
entity |
| Predicate | hasCountyNumberInTennessee |
P57338
|
FINISHED |
| Object | 33 |
—
|
LITERAL 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: 33 | Statement: [Hamilton County, Tennessee, hasCountyNumberInTennessee, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCountyNumberInTennessee Context triple: [Hamilton County, Tennessee, hasCountyNumberInTennessee, 33]
-
A.
hasCountyCode
Indicates that an entity is associated with a specific county identified by a standardized county code.
-
B.
numberPerCounty
Indicates the quantity or count of something associated with each individual county.
-
C.
hasCountyNumberInSouthDakota
Indicates that an entity is associated with a specific officially assigned county number within the state of South Dakota.
-
D.
includesCounty
Indicates that a larger geographic or administrative region contains or encompasses a specific county within its boundaries.
-
E.
startCounty
Indicates the county in which something (such as an event, route, or process) begins or originates.
- F. None of above. chosen
Provenance (4 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b78b8481909d79131723d4be22 |
completed | March 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69bd521edd00819099dfccaa65dddd61 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b3e4c88190a7ade3d0ed0ab606 |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:04 p.m.