Triple
T20931471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turan |
E515480
|
entity |
| Predicate | associatedWithCharacter |
P1481
|
FINISHED |
| Object | Farud |
—
|
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: Farud | Statement: [Turan, associatedWithCharacter, Farud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Farud Context triple: [Turan, associatedWithCharacter, Farud]
-
A.
Farud
chosen
Farud is a character in the Persian epic Shahnameh, known as the son of the legendary king Kay Kavus and for his tragic, heroic death in battle.
-
B.
Farhual
Farhual is a regional dialect of the Hakha Chin language spoken by Chin communities in parts of Myanmar and neighboring areas.
-
C.
Faris
Faris is a masculine given name of Arabic origin commonly meaning "knight" or "horseman."
-
D.
Faris
Faris is the surname of American actress and comedian Anna Faris, known for her roles in the Scary Movie film series and various comedy projects.
-
E.
Rauf
Rauf is a masculine given name commonly used in various Muslim-majority cultures, derived from Arabic and meaning "compassionate" or "kind."
- 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_69e0b4fb431c8190b9d40e6a72f0cc87 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f65681b4819083c7ef6b44ba4bdb |
completed | April 21, 2026, 4 a.m. |
Created at: April 16, 2026, 12:49 p.m.