Triple
T9499492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delovoy Tsentr |
E229097
|
entity |
| Predicate | hasNameTransliteration |
P5923
|
FINISHED |
| Object | Delovoy Tsentr |
E229097
|
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: Delovoy Tsentr | Statement: [Delovoy Tsentr, hasNameTransliteration, Delovoy Tsentr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Delovoy Tsentr Context triple: [Delovoy Tsentr, hasNameTransliteration, Delovoy Tsentr]
-
A.
Delovoy Tsentr
chosen
Delovoy Tsentr is a Moscow Metro station serving the Moscow International Business Center, providing access to one of the city's main commercial and office districts.
-
B.
Centrum
Centrum is the central district and main urban core of the Dutch municipality of Ridderkerk.
-
C.
Centrum
Centrum is the historic city center district of Amsterdam, known for its canals, landmarks, and bustling markets.
-
D.
Centrum
Centrum is the central urban district and main commercial area of the Dutch city of Meppel.
-
E.
Tekhnopark
Tekhnopark is a Moscow Metro station on the Zamoskvoretskaya Line serving the Technopark technology and business district in southern Moscow.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983a94c48190a7ddf95a953c4ecc |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d412a008190adc82e1e3d56d107 |
completed | April 4, 2026, 3:24 p.m. |
Created at: March 30, 2026, 7:56 p.m.