Triple
T5968229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sousse |
E132805
|
entity |
| Predicate | historicalName |
P65
|
FINISHED |
| Object | Susa (medieval) |
E163800
|
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: Susa (medieval) | Statement: [Sousse, historicalName, Susa (medieval)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Susa (medieval) Context triple: [Sousse, historicalName, Susa (medieval)]
-
A.
Susa
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
chosen
Susa is an ancient town in the Piedmont region of northwestern Italy, historically significant as a key Alpine gateway between Italy and France.
-
C.
Sanjar
Sanjar was a prominent 12th-century Seljuk ruler who governed the eastern provinces of the empire and is often regarded as its last great sultan.
-
D.
Gundeshapur
Gundeshapur was a prominent Sasanian city in southwestern Iran renowned as a major center of learning, medicine, and philosophy in late antiquity.
-
E.
Sultaniyeh
Sultaniyeh is a historic city in northwestern Iran best known for its UNESCO-listed Ilkhanid-era mausoleum, one of the largest brick domes in the world.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03a3f612481908744cb645f2ede1d |
completed | March 22, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e40506848190843971e772d56054 |
completed | March 23, 2026, 6:56 a.m. |
Created at: March 22, 2026, 4:03 p.m.