Triple
T5591862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morton H. Meyerson |
E146896
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Morton |
E377038
|
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: Morton | Statement: [Morton H. Meyerson, givenName, Morton]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morton Context triple: [Morton H. Meyerson, givenName, Morton]
-
A.
Morton
Morton is a timid yet loyal mouse-like creature in the animated film "Horton Hears a Who!" who serves as Horton's cautious but supportive friend.
-
B.
Morton
chosen
Morton is the given first name of Mort Sahl, the influential Canadian-American stand-up comedian known for his pioneering political satire.
-
C.
Moston
Moston is a residential district in north Manchester, England, known for its mix of traditional terraced housing, local parks, and community amenities.
-
D.
Manton
Manton is a neighborhood and village area located within Providence County in the state of Rhode Island.
-
E.
Seymour
Seymour is a masculine given name of English origin that has been borne by various notable figures in fields such as business, politics, and the arts.
- 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_69c009036c408190981a8d690b679b67 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020a3365c8190bd223226c0a6969f |
completed | March 22, 2026, 5:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0286852148190ad4975fe746d7001 |
completed | March 22, 2026, 5:35 p.m. |
Created at: March 22, 2026, 3:38 p.m.