Triple
T19081035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Esther and the King |
E467031
|
entity |
| Predicate | setInPlace |
P1957
|
FINISHED |
| Object | Susa |
—
|
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: Susa | Statement: [Esther and the King, setInPlace, Susa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susa Context triple: [Esther and the King, setInPlace, Susa]
-
A.
Susa
chosen
Susa was an ancient city in southwestern Iran that served as a major political and administrative center for several empires, including the Achaemenid Persians.
-
B.
Susa
Susa is an ancient town in the Piedmont region of northwestern Italy, historically significant as a key Alpine gateway between Italy and France.
-
C.
Susa
Susa is a coastal town in northeastern Libya known for its ancient Greek and Roman archaeological remains and its location along the Mediterranean Sea.
-
D.
Ecbatana
Ecbatana is an ancient city, traditionally identified with the capital of the Median Empire in northwestern Iran, known from classical sources and biblical texts.
-
E.
Arsanjan
Arsanjan is a small city in southern Iran known for its agricultural activities and location within the historical and culturally rich Fars region.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2e8f8148190942cca6dd3e30caf |
completed | April 20, 2026, 8:25 a.m. |
Created at: April 10, 2026, 12:04 p.m.