Triple
T18823906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anson Mount |
E460333
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Darah Trang |
—
|
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: Darah Trang | Statement: [Anson Mount, spouse, Darah Trang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Darah Trang Context triple: [Anson Mount, spouse, Darah Trang]
-
A.
Darah Trang
chosen
Darah Trang is a professional photographer and the wife of American actor Anson Mount.
-
B.
Dang Me
"Dang Me" is a 1964 novelty country song by Roger Miller that became one of his signature hits and helped establish his reputation for witty, humorous songwriting.
-
C.
Sanguem
Sanguem is a town and administrative taluka in the Indian state of Goa, known for its rural landscape, waterfalls, and proximity to wildlife sanctuaries.
-
D.
Tai Yai
Tai Yai refers to the Shan people, a Tai ethnic group primarily inhabiting Myanmar’s Shan State and neighboring regions of Southeast Asia.
-
E.
Daji
Daji is a legendary figure in Chinese mythology, often depicted as a beautiful but malevolent consort whose influence is blamed for the downfall of the Shang dynasty.
- 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_69d8dcf94c288190a06dea029ae4b223 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a6bce5588190bd0aefcd0c51edad |
completed | April 20, 2026, 4:08 a.m. |
Created at: April 10, 2026, 11:56 a.m.