Triple
T10929926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Green Line |
E258174
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object | The Green Stripe |
E785528
|
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: The Green Stripe | Statement: [The Green Line, title, The Green Stripe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Green Stripe Context triple: [The Green Line, title, The Green Stripe]
-
A.
The Green Stripe
chosen
The Green Stripe is a 1905 Fauvist portrait by Henri Matisse of his wife Amélie, notable for its bold use of a green line to divide and model the face.
-
B.
Red, Black & Green
"Red, Black & Green" is a 1973 jazz-funk album by vibraphonist Roy Ayers that blends soulful grooves with socially conscious themes.
-
C.
La Bicolor
La Bicolor is the popular nickname of the Guatemala national football team, referring to its traditional two-colored kit.
-
D.
Stripes
Stripes is a 1981 American comedy film starring Bill Murray as a slacker who impulsively joins the U.S. Army, leading to a series of irreverent misadventures.
-
E.
Racing Stripes
Racing Stripes is a 2005 family sports comedy film about a young zebra who dreams of becoming a racehorse.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7709f92088190a15ae3638d3b14fb |
completed | April 9, 2026, 9:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2175711d4819088f93bdf64ba4d3f |
completed | April 17, 2026, 11:19 a.m. |
Created at: April 8, 2026, 9:22 p.m.