Triple
T5549010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temür Khan |
E145478
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Dadu |
E139082
|
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: Dadu | Statement: [Temür Khan, capital, Dadu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dadu Context triple: [Temür Khan, capital, Dadu]
-
A.
Dadu
chosen
Dadu was the Yuan dynasty capital city established by Kublai Khan on the site of present-day Beijing, serving as the political and cultural center of his empire.
-
B.
Dadu’a
Dadu’a is an indigenous local language spoken on Atauro Island, part of Timor-Leste.
-
C.
Le Duan
Le Duan was a Vietnamese communist revolutionary and politician who served as the de facto top leader of North Vietnam during most of the Vietnam War and later of a reunified Vietnam.
-
D.
Shaowu
Shaowu is a county-level city in northwestern Fujian Province, China, known for its mountainous landscape and location along the upper reaches of the Min River.
-
E.
Kwang-chou
Kwang-chou is an alternative romanization of Guangzhou, the major port city and economic hub in southern China historically known in the West as Canton.
- 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_69c008fb879c81909f5bfa56fadc1d46 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fe143ec8190bb67d2530c92a419 |
completed | March 22, 2026, 4:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04cf6d9f48190a3ee3446973c7381 |
completed | March 22, 2026, 8:11 p.m. |
Created at: March 22, 2026, 3:35 p.m.