Triple
T15347448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deborah Lautner |
E366959
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Taylor Lautner |
E71820
|
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: Taylor Lautner | Statement: [Deborah Lautner, relative, Taylor Lautner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taylor Lautner Context triple: [Deborah Lautner, relative, Taylor Lautner]
-
A.
Taylor Lautner
chosen
Taylor Lautner is an American actor best known for playing werewolf Jacob Black in the Twilight film series.
-
B.
Luke Hemsworth
Luke Hemsworth is an Australian actor best known for his role as Ashley Stubbs in the HBO science-fiction series "Westworld."
-
C.
Liam Hemsworth
Liam Hemsworth is an Australian actor known for his role as Gale Hawthorne in "The Hunger Games" film series and for his high-profile relationship with singer Miley Cyrus.
-
D.
Zac Efron
Zac Efron is an American actor and singer who rose to fame with Disney’s "High School Musical" series and has since starred in a variety of film and television roles.
-
E.
John Harding
John Harding is an actor known for appearing in the classic comedy film "Please Don’t Eat the Daisies."
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e1749bc8190a8b9cbcb27288a5b |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1341033881909121ade33cecaf50 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:17 a.m.