Triple
T9927887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John C. Mather |
E187968
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Mather |
E665026
|
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: Mather | Statement: [John C. Mather, familyName, Mather]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mather Context triple: [John C. Mather, familyName, Mather]
-
A.
Mather
chosen
Mather is a surname most notably associated with the prominent New England Puritan minister and author Cotton Mather and his influential family.
-
B.
Arbella
Arbella was the flagship that carried John Winthrop and other Puritan settlers to New England during the Great Migration of 1630.
-
C.
Revere
Revere is a surname most notably associated with American historical figure Paul Revere and various other individuals in politics, arts, and public life.
-
D.
Kittredge
Kittredge is an English-language surname borne by various notable figures, including American writer Charmian Kittredge London.
-
E.
Mather Zickel
Mather Zickel is an American actor known for his work in film and television, including roles in projects like "Rachel Getting Married" and various comedy series.
- 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_69ca82b22a688190b52c75bd48429c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb59d7ad08190982a1584547190bd |
completed | April 2, 2026, 12:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d20e1eace88190a591cbab02153869 |
completed | April 5, 2026, 7:24 a.m. |
Created at: March 30, 2026, 8:43 p.m.