Triple
T4615849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air India |
E100865
|
entity |
| Predicate | CEO |
P537
|
FINISHED |
| Object | Campbell Wilson |
E458482
|
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: Campbell Wilson | Statement: [Air India, CEO, Campbell Wilson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Campbell Wilson Context triple: [Air India, CEO, Campbell Wilson]
-
A.
Campbell Wilson
chosen
Campbell Wilson is an airline executive who serves as the chief executive officer and managing director of Air India.
-
B.
Melissa George
Melissa George is an Australian actress known for her roles in both film and television, including prominent performances in horror and thriller genres.
-
C.
Dakota Johnson
Dakota Johnson is an American actress best known for starring as Anastasia Steele in the film adaptation of the erotic romance novel "Fifty Shades of Grey" and its sequels.
-
D.
Jessica Chastain
Jessica Chastain is an acclaimed American actress known for her versatile performances in films such as "Zero Dark Thirty," "The Help," and "Molly's Game."
-
E.
Penelope Ann Miller
Penelope Ann Miller is an American actress known for her roles in films such as "Carlito's Way," "The Artist," and "Kindergarten Cop."
- 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_69bd43cf363c819087fd5ab441b4a3f4 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59df3c3c8190be5db000f831d322 |
completed | March 20, 2026, 2:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be035a44f08190900bc6898a40e4e9 |
completed | March 21, 2026, 2:32 a.m. |
Created at: March 20, 2026, 1:12 p.m.