Triple
T20388586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Langoliers |
E498023
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Edward J. Pei |
—
|
NE NERFINISHED |
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: Edward J. Pei | Statement: [The Langoliers, cinematographyBy, Edward J. Pei]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Edward J. Pei Context triple: [The Langoliers, cinematographyBy, Edward J. Pei]
-
A.
Edward J. Pei
chosen
Edward J. Pei is a film cinematographer known for his work on feature films such as the biographical drama "Why Do Fools Fall in Love."
-
B.
Philip S. Yu
Philip S. Yu is a prominent computer scientist known for his influential contributions to data mining, databases, and big data analytics.
-
C.
Mung Chiang
Mung Chiang is an engineer and academic leader known for his work in electrical and computer engineering and for serving as president of Purdue University.
-
D.
W. John Kao
W. John Kao is an academic leader and scholar who serves as president of National Tsing Hua University in Taiwan.
-
E.
Kuo-Chen Huang
Kuo-Chen Huang was a physicist whose work on electron–phonon coupling in solids led to the formulation of the Huang–Rhys factor in solid-state spectroscopy.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790d9e5881908bde7da9e5e541a0 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.