Triple
T15656574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parkland |
E376456
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Tom Welling |
E219115
|
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: Tom Welling | Statement: [Parkland, castMember, Tom Welling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Welling Context triple: [Parkland, castMember, Tom Welling]
-
A.
Tom Welling
chosen
Tom Welling is an American actor best known for playing Clark Kent/Superman on the television series "Smallville."
-
B.
Shawn Ashmore
Shawn Ashmore is a Canadian actor best known for playing Iceman in the X-Men film series and for roles in television shows such as The Following and The Boys.
-
C.
Taylor Lautner
Taylor Lautner is an American actor best known for playing werewolf Jacob Black in the Twilight film series.
-
D.
Stephen Amell
Stephen Amell is a Canadian actor best known for portraying Oliver Queen/Green Arrow in the television series "Arrow."
-
E.
Wes Bentley
Wes Bentley is an American actor known for his breakout role in "American Beauty" and appearances in films like "The Hunger Games" and "Interstellar."
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04ef1f83c8190bbf65eed162cbd55 |
completed | April 16, 2026, 2:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff67994fbc819090f2da267888e8fb |
completed | May 9, 2026, 4:58 p.m. |
Created at: April 10, 2026, 4:15 a.m.