Triple
T20649834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anas al-Abdah |
E507459
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Anas |
—
|
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: Anas | Statement: [Anas al-Abdah, givenName, Anas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anas Context triple: [Anas al-Abdah, givenName, Anas]
-
A.
Anas
chosen
Anas is a masculine given name of Arabic origin commonly used across the Muslim world.
-
B.
Anas acuta
Anas acuta, commonly known as the northern pintail, is a widespread and elegant dabbling duck species recognized for its slender neck, long pointed tail, and extensive migratory range across the Northern Hemisphere.
-
C.
Anser
Anser is a genus of waterfowl that includes the true geese of the Northern Hemisphere, such as the greylag and white-fronted geese.
-
D.
Bico de Pato
Bico de Pato is a tight, slow-speed hairpin-style corner at Brazil’s Autódromo José Carlos Pace (Interlagos) known for heavy braking and overtaking opportunities.
-
E.
Goose
Goose is a common nickname most famously associated with Nick "Goose" Bradshaw, the loyal radar intercept officer in the film "Top Gun."
- 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_69e0b4bf58c081908e52a4500e03ff83 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af2133048190a6308074a3b3347e |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.