Triple
T9163493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Pilkington |
E219887
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Pilkington |
E337781
|
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: Pilkington | Statement: [Karl Pilkington, familyName, Pilkington]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pilkington Context triple: [Karl Pilkington, familyName, Pilkington]
-
A.
Pilkington glass company
chosen
Pilkington glass company is a major British glass manufacturer renowned for pioneering the float glass process and supplying glass products worldwide.
-
B.
Corning
Corning is a small city in Tehama County, California, known historically for its olive production and agricultural economy.
-
C.
Corning
Corning is a small city in New York State best known as the longtime home of Corning Incorporated and its historic glassmaking and museum.
-
D.
Libbey Glass
Libbey Glass is a prominent American glassware manufacturer known for producing a wide range of tableware and drinkware products for both consumer and commercial markets.
-
E.
Saint-Gobain
Saint-Gobain is a major French multinational corporation specializing in the production and distribution of construction materials and high-performance solutions for buildings and industry.
- 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_69ca83e3633c81908688a9fa2306ba99 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaa2d6628819084ac4734650fe912 |
completed | April 1, 2026, 5:16 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0547df750819095853f21cf740c63 |
completed | April 3, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:21 p.m.