Triple
T4163915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrei Linde |
E84395
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Linde |
E149805
|
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: Linde | Statement: [Andrei Linde, familyName, Linde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Linde Context triple: [Andrei Linde, familyName, Linde]
-
A.
Linde
chosen
Linde is a given name, often used in Germanic and Scandinavian countries, that is related to or derived from the name Linda.
-
B.
Matheson
Matheson is a surname of Scottish origin borne by various notable individuals, including acclaimed American writer Richard Matheson.
-
C.
Arkema
Arkema is a French multinational specialty chemicals and advanced materials company known for its innovations in adhesives, coatings, and performance polymers.
-
D.
Bühler
Bühler is a German-language surname borne by various notable individuals across fields such as politics, sports, and academia.
-
E.
Airco
Airco was a British aircraft manufacturer best known for producing military aircraft during World War I, including the successful DH series of biplanes.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02a9bf348190b99cecd19fe65779 |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f478c948190a997e006015e588d |
completed | March 14, 2026, 3:31 p.m. |
Created at: March 9, 2026, 3:44 p.m.