Triple
T6945884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doris Lessing |
E160797
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Kermanshah, Persia |
E210929
|
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: Kermanshah, Persia | Statement: [Doris Lessing, placeOfBirth, Kermanshah, Persia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kermanshah, Persia Context triple: [Doris Lessing, placeOfBirth, Kermanshah, Persia]
-
A.
Kermanshah
chosen
Kermanshah is a major city in western Iran known for its rich Kurdish culture and proximity to important historical and archaeological sites.
-
B.
Kerman
Kerman is a small city in California’s San Joaquin Valley, known for its agricultural economy and location west of Fresno.
-
C.
Kerman
Kerman is the surname of Piper Kerman, the American author whose memoir inspired the television series "Orange Is the New Black."
-
D.
Kerman
Kerman is a major city in southeastern Iran known for its rich history, traditional bazaars, and proximity to desert landscapes.
-
E.
Qazvin, Iran
Qazvin is a historic city in northwestern Iran known for its rich Persian architectural heritage, including numerous mosques, caravanserais, and traditional bazaars.
- 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_69c68850419081909fb426b8f5a304c7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da8a65c48190b6862fc60f6c7f7a |
completed | March 27, 2026, 7:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7586b6f0c8190a6caad7d020e9c4d |
completed | March 28, 2026, 4:26 a.m. |
Created at: March 27, 2026, 2:28 p.m.