Triple
T20578750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellowjackets |
E505294
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Four Corners |
—
|
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: Four Corners | Statement: [Yellowjackets, notableWork, Four Corners]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Four Corners Context triple: [Yellowjackets, notableWork, Four Corners]
-
A.
Four Corners
chosen
Four Corners is a television drama series featuring Justin Chambers in a prominent role.
-
B.
Four Corners
Four Corners is a residential neighborhood that serves as the community setting for Pine Crest Elementary School.
-
C.
Four Corners
Four Corners is the unique point in the United States where the states of New Mexico, Arizona, Utah, and Colorado meet, marked by a monument that attracts many visitors.
-
D.
Four Corners col
Four Corners col is a mountain pass and trail junction in the Adirondack High Peaks region that serves as a key access point for nearby summits such as Skylight.
-
E.
The First 48
The First 48 is a true-crime documentary television series that follows real homicide investigations during the critical first two days after a murder.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a90cc22c8190969e3a21ae92f1c9 |
completed | April 20, 2026, 10:30 p.m. |
Created at: April 16, 2026, 11:39 a.m.