Triple
T16018042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henry Patterson |
E388517
|
entity |
| Predicate | hasPseudonym |
P3799
|
FINISHED |
| Object | Hugh Marlowe |
E21702
|
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: Hugh Marlowe | Statement: [Henry Patterson, hasPseudonym, Hugh Marlowe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hugh Marlowe Context triple: [Henry Patterson, hasPseudonym, Hugh Marlowe]
-
A.
Hugh Marlowe
chosen
Hugh Marlowe was an American film, television, and stage actor best known for his roles in classic mid-20th-century movies and popular TV series.
-
B.
Christopher Marlowe
Christopher Marlowe was a pioneering Elizabethan playwright and poet whose works, including "Doctor Faustus" and "Tamburlaine," helped shape the development of English Renaissance drama.
-
C.
Marlowe
Marlowe is a neo-noir crime thriller film centered on the iconic private detective Philip Marlowe, adapted from John Banville’s novel "The Black-Eyed Blonde."
-
D.
Marlowe
Marlowe is an unincorporated community located in Berkeley County, West Virginia, known for its rural setting near the Potomac River.
-
E.
Marlowe
Marlowe is a feminine given name that has gained popularity in recent years, often chosen for its literary and sophisticated sound.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18296a7008190b72ab2ab02d0fbc9 |
completed | April 17, 2026, 12:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffcf2a4b0c819094f629c65cf8f880 |
completed | May 10, 2026, 12:19 a.m. |
Created at: April 10, 2026, 4:55 a.m.