Triple
T15781935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yazdegerd III |
E382638
|
entity |
| Predicate | deathPlace |
P21
|
FINISHED |
| Object | Marw |
E792638
|
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: Marw | Statement: [Yazdegerd III, deathPlace, Marw]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marw Context triple: [Yazdegerd III, deathPlace, Marw]
-
A.
Marw
chosen
Marw (Merv) was an important ancient city in Khorasan, serving as a major political, military, and cultural center in early Islamic and pre-Islamic Central Asia.
-
B.
Modasa
Modasa is a town in the Indian state of Gujarat that serves as the administrative headquarters of Aravalli district.
-
C.
Naab
The Naab is a river in Bavaria, Germany, that flows through the Upper Palatinate region before joining the Danube.
-
D.
Anadia
Anadia is a municipality and town in Portugal known for its wine production and thermal spas, located in the country's Centro Region.
-
E.
Mima City
Mima City is a municipality in western Tokushima Prefecture, Japan, known for its historic townscapes, traditional indigo dyeing culture, and scenic rural landscapes.
- 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_69d86da09a10819082fe9797b23e4664 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e05400716881909bc43212c8ea54d5 |
completed | April 16, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff90a2476c8190a153fb47cb4e7708 |
completed | May 9, 2026, 7:53 p.m. |
Created at: April 10, 2026, 4:48 a.m.