Triple
T3858704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grown Ups |
E90082
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Fred Wolf |
E389185
|
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: Fred Wolf | Statement: [Grown Ups, writer, Fred Wolf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fred Wolf Context triple: [Grown Ups, writer, Fred Wolf]
-
A.
Fred Wolf
chosen
Fred Wolf is an American comedy writer, director, and producer known for his work on films like "Grown Ups 2" and for his contributions to "Saturday Night Live."
-
B.
Ron Huldai
Ron Huldai is an Israeli politician and former fighter pilot best known for serving as the long-time mayor of Tel Aviv.
-
C.
Edmund Stoiber
Edmund Stoiber is a German conservative politician who served for many years as Minister-President of Bavaria and became a prominent national figure as the CDU/CSU candidate for chancellor in 2002.
-
D.
Michael Schroeder
Michael Schroeder is a software developer best known for his work on the GNU Screen terminal multiplexer.
-
E.
Michael Schultz
Michael Schultz is an American film and television director best known for his influential work on 1970s comedies and dramas, including the cult classic "Car Wash."
- 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_69aed95b3c088190a8f85d19e6070599 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec1e68f88190941c39221486f6ae |
completed | March 9, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b504228220819082e11b316ba79b08 |
completed | March 14, 2026, 6:45 a.m. |
Created at: March 9, 2026, 3:19 p.m.