Triple
T15619771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Issy-les-Moulineaux |
E375517
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object | Taicang |
E258088
|
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: Taicang | Statement: [Issy-les-Moulineaux, hasTwinTown, Taicang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taicang Context triple: [Issy-les-Moulineaux, hasTwinTown, Taicang]
-
A.
Changshu
Changshu is a county-level city in Jiangsu Province, eastern China, known for its textile industry, historic sites, and location near Suzhou and Shanghai.
-
B.
Taicang, Jiangsu
chosen
Taicang, Jiangsu is a county-level city under Suzhou in eastern China, known for its developed port on the Yangtze River estuary and its strong manufacturing and logistics industries.
-
C.
Xiantao
Xiantao is a county-level city in central China’s Hubei province, known for its location on the Jianghan Plain and its role as a regional agricultural and industrial center.
-
D.
Taizhou
Taizhou is a prefecture-level city in eastern China known for its historical heritage and location along the Yangtze River in Jiangsu province.
-
E.
Taizhou
Taizhou is a coastal prefecture-level city in eastern China known for its manufacturing industry, port facilities, and location along the East China Sea.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e997ce481909b2f10d25705fbc6 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ece07608190a705f108c8c2979a |
completed | May 9, 2026, 5:28 p.m. |
Created at: April 10, 2026, 4:13 a.m.