Triple
T3540613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | May |
E74874
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Robert May |
E11183
|
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: Robert May | Statement: [May, hasNotableBearer, Robert May]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Robert May Context triple: [May, hasNotableBearer, Robert May]
-
A.
Robert May
chosen
Robert May was a prominent theoretical ecologist and mathematical biologist known for his influential work on population dynamics and the application of chaos theory to ecology.
-
B.
Walter Connolly
Walter Connolly was an American character actor of the 1930s known for his comic and often blustery supporting roles in Hollywood films.
-
C.
Robert L. May
Robert L. May was an American copywriter and author best known for creating the Christmas character Rudolph the Red-Nosed Reindeer.
-
D.
Geoffrey Streatfeild
Geoffrey Streatfeild is a British actor known for his work in film, television, and theatre, including roles in productions such as "The Thick of It" and "Spooks."
-
E.
Douglas Clifton Brown
Douglas Clifton Brown was a British Conservative politician who served as Speaker of the House of Commons during the Second World War and the early postwar period.
- 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_69ad85d274cc8190ab59c97298a1cfbf |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbf729000819086e4fdba9e73e198 |
completed | March 8, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bd7fa3881909fee11cc6f4af7ea |
completed | March 13, 2026, 4 a.m. |
Created at: March 8, 2026, 3:20 p.m.