Triple
T2152007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lukas Haas |
E47800
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Lukas Haas |
E47800
|
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: Lukas Haas | Statement: [Lukas Haas, name, Lukas Haas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lukas Haas Context triple: [Lukas Haas, name, Lukas Haas]
-
A.
Lukas Haas
chosen
Lukas Haas is an American actor known for his early breakthrough role in "Witness" (1985) and a diverse career spanning independent films and major Hollywood productions.
-
B.
Sebastian Maltz
Sebastian Maltz is an actor known for his role in the television drama series "Patrick Melrose."
-
C.
Nico Habermann
Nico Habermann was a German-American computer scientist known for his contributions to programming languages, operating systems, and software engineering, and for his influential academic leadership at Carnegie Mellon University.
-
D.
Lukas
Lukas is a masculine given name commonly used in various European countries, often associated with the biblical name Luke.
-
E.
Nicholas Hannen
Nicholas Hannen was a British stage and film actor known for his classical performances, including roles in mid-20th-century Shakespearean adaptations.
- 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_69a88a1d1fd8819088b34990d69a712f |
completed | March 4, 2026, 7:38 p.m. |
| NER | Named-entity recognition | batch_69abbe48ad148190a7d6cc88fd38a660 |
completed | March 7, 2026, 5:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58e0e1b481909545e8e6d861adfd |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:44 p.m.