Triple
T8203514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muslim conquest of Persia |
E191633
|
entity |
| Predicate | capturedCity |
P8411
|
FINISHED |
| Object | Merv |
E85087
|
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: Merv | Statement: [Muslim conquest of Persia, capturedCity, Merv]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Merv Context triple: [Muslim conquest of Persia, capturedCity, Merv]
-
A.
Merv
chosen
Merv was an important ancient oasis city in Central Asia that flourished as a key commercial and cultural hub along the Silk Road.
-
B.
Wasilla
Wasilla is a small city in south-central Alaska known as part of the Anchorage metropolitan area and for being the hometown of former governor Sarah Palin.
-
C.
Rushan
Rushan is a county-level coastal city in eastern Shandong Province, China, known for its fishing industry, beaches, and marine-based economy.
-
D.
Farshut
Farshut is a town in Upper Egypt known as an agricultural and local commercial center within the Qena region.
-
E.
Lavon
Lavon is a Hebrew surname most notably associated with Israeli politician Pinhas Lavon, who served as Israel’s Minister of Defense in the 1950s.
- 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_69ca82c7f3e08190857bf1fc63b2a10c |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb5df9cac08190a890ded4c7fbd393 |
completed | March 31, 2026, 5:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccedcb45d0819099c13bd455526974 |
completed | April 1, 2026, 10:04 a.m. |
Created at: March 30, 2026, 5:43 p.m.