Triple
T2139962
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inside Out |
E46737
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Patrick Lin |
E236528
|
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: Patrick Lin | Statement: [Inside Out, cinematographyBy, Patrick Lin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Patrick Lin Context triple: [Inside Out, cinematographyBy, Patrick Lin]
-
A.
Patrick Lin
chosen
Patrick Lin is a cinematographer and layout artist best known for his work on Pixar animated films, including serving as director of photography on "Up."
-
B.
Howie Choset
Howie Choset is an American roboticist known for his work on snake robots and modular robotics, and a professor at Carnegie Mellon University.
-
C.
Rodney Brooks
Rodney Brooks is an influential roboticist and AI researcher known for pioneering behavior-based robotics and co-founding iRobot and Rethink Robotics.
-
D.
Wolfram Burgard
Wolfram Burgard is a German computer scientist and roboticist known for his influential work in probabilistic robotics, autonomous navigation, and artificial intelligence.
-
E.
Pieter Abbeel
Pieter Abbeel is a Belgian-American computer scientist and professor at UC Berkeley known for his influential work in robotics and deep reinforcement learning.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbe025d3c81908bcb33a7ff09eae8 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae58d5535c8190b59293afe3a10834 |
completed | March 9, 2026, 5:21 a.m. |
Created at: March 4, 2026, 7:44 p.m.