Triple
T4645544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Hunt Morgan |
E101763
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Morgan
Morgan is a common English surname borne by numerous notable individuals across fields such as science, finance, and entertainment.
|
E459318
|
NE FINISHED |
How this triple was built (4 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: [Thomas Hunt Morgan, familyName, Morgan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morgan Context triple: [Thomas Hunt Morgan, familyName, 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
Morgan is a given name most famously associated with acclaimed American actor and narrator Morgan Freeman.
-
D.
Morgan
Morgan is a 2016 science fiction horror film about a genetically engineered human hybrid whose violent behavior leads to a crisis among the scientists who created her.
-
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. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Morgan Triple: [Thomas Hunt Morgan, familyName, Morgan]
Generated description
Morgan is a common English surname borne by numerous notable individuals across fields such as science, finance, and entertainment.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Morgan Target entity description: Morgan is a common English surname borne by numerous notable individuals across fields such as science, finance, and entertainment.
-
A.
Morgan
Morgan is a given name most famously associated with acclaimed American actor and narrator Morgan Freeman.
-
B.
Morgan
Morgan is a prominent American banking and finance family name most famously associated with financier J. P. Morgan and the powerful House of Morgan banking dynasty.
-
C.
Morgan
Morgan is the middle name of the renowned English novelist and essayist E. M. Forster.
-
D.
Morgan
Morgan is a 2016 science fiction horror film about a genetically engineered human hybrid whose violent behavior leads to a crisis among the scientists who created her.
-
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. chosen
Provenance (5 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_69bd43d3bc7c81908f81fcf380476b0f |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd623815288190b21cf59a3786363d |
completed | March 20, 2026, 3:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfadc5dc081908d56a49895105efb |
completed | March 21, 2026, 1:56 a.m. |
| NEDg | Description generation | batch_69bdfc6751988190917ec53a8e2e27ec |
completed | March 21, 2026, 2:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be009e6c488190b18e1b2b4b34ecef |
completed | March 21, 2026, 2:21 a.m. |
Created at: March 20, 2026, 1:14 p.m.