Triple
T6143428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange S.A. |
E137016
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object | Orange |
E137016
|
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: [Orange S.A., hasAbbreviation, Orange]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange Context triple: [Orange S.A., hasAbbreviation, Orange]
-
A.
Orange
chosen
Orange is a major French multinational telecommunications company providing mobile, internet, and other digital services across numerous countries.
-
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 the nickname and primary identity of Syracuse University's athletic teams, especially its prominent men's basketball program.
-
E.
Orange
Orange is one of the color-coded lines of Miami’s Metrorail system, serving as a distinct route that includes Brickell station among its stops.
- 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_69c008a2c6308190a56519b22d55d083 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cb50cb0819081ac64becf7aaf55 |
completed | March 22, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c141777d808190ad36b574356ca715 |
completed | March 23, 2026, 1:34 p.m. |
Created at: March 22, 2026, 4:16 p.m.