Triple
T8875247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morgan Eastwood |
E211261
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Morgan |
E684732
|
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: Morgan | Statement: [Morgan Eastwood, givenName, Morgan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morgan Context triple: [Morgan Eastwood, givenName, Morgan]
-
A.
Morgan
Morgan is the middle name of the renowned English novelist and essayist E. M. Forster.
-
B.
Morgan
Morgan is a Chicago 'L' rapid transit station on the Near West Side serving the city's Pink and Green Lines.
-
C.
Morgan
chosen
Morgan is a given name used by the American documentary filmmaker Morgan Neville.
-
D.
Morgan
Morgan is a prominent law firm that forms part of the larger legal practice Lloyd, Morgan & Jones.
-
E.
Morgan
Morgan is the party that successfully defended the constitutionality of a key provision of the Voting Rights Act in the landmark U.S. Supreme Court case Katzenbach v. Morgan.
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc614565788190aa14535760df88c8 |
completed | April 1, 2026, 12:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0f9714c8190909587eecbb10e1a |
completed | April 3, 2026, 11:14 a.m. |
Created at: March 30, 2026, 6:52 p.m.