Triple
T17305265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patrick Marber |
E420143
|
entity |
| Predicate | wrotePlay |
P2831
|
FINISHED |
| Object | Howard Katz |
—
|
NE NERFINISHED |
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: Howard Katz | Statement: [Patrick Marber, wrotePlay, Howard Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Katz Context triple: [Patrick Marber, wrotePlay, Howard Katz]
-
A.
Howard Katz
chosen
Howard Katz is a darkly comic stage play by British playwright Patrick Marber that follows the midlife crisis and spiritual unraveling of a once-successful talent agent.
-
B.
Don Katz
Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
-
C.
Howard Klausner
Howard Klausner is an American screenwriter best known for co-writing the Clint Eastwood film "Space Cowboys" and working on various other feature and television projects.
-
D.
Howard Klein
Howard Klein is a television producer known for his work on acclaimed series such as Carnivàle.
-
E.
Allan Katz
Allan Katz is a television writer and producer best known for his work on classic American sitcoms.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e438fe1d408190a429d1dba50d0c58 |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 5:43 a.m.