Triple
T16333301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chalon-Orange |
E396609
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Orange |
E3952
|
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: Orange | Statement: [Chalon-Orange, region, Orange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange Context triple: [Chalon-Orange, region, Orange]
-
A.
Orange
chosen
Orange is a historic town in southeastern France best known for giving its name and origin to the Dutch royal House of Orange-Nassau.
-
B.
Orange
Orange is a regional city in the Central Tablelands of New South Wales, Australia, known for its cool-climate wines, agriculture, and growing tourism industry.
-
C.
Orange
Orange is a small suburban village in Cuyahoga County, Ohio, known for its residential character and proximity to the Cleveland metropolitan area.
-
D.
Orange
Orange is a citrus-flavored sports drink variety known for its bright, tangy taste and association with energy and hydration.
-
E.
Orange
Orange was the original name of the town now known as Hillsborough in North Carolina, reflecting its early colonial-era identity.
- 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_69d87f255b788190a400eba031dd85d8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2c4e1da1081909bec6e77e6109dce |
completed | April 17, 2026, 11:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0026173dc081909e00f6647d1f68b3 |
completed | May 10, 2026, 6:30 a.m. |
Created at: April 10, 2026, 5:07 a.m.