Triple
T23638729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cambaluc |
E583824
|
entity |
| Predicate | predecessorCityName |
P152984
|
FINISHED |
| Object | Zhongdu |
—
|
NE NERFINISHED |
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: Zhongdu | Statement: [Cambaluc, predecessorCityName, Zhongdu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predecessorCityName Context triple: [Cambaluc, predecessorCityName, Zhongdu]
-
A.
previousCity
Indicates that one city was the immediately preceding location visited or lived in before another city.
-
B.
teamPredecessorCity
Indicates that one sports team previously based in a given city is the predecessor or earlier incarnation of another team in that city.
-
C.
formerCityName
Indicates that an entity was previously known by a different city name in the past.
-
D.
hasPredecessorNameInCity
Indicates that an entity has a predecessor (e.g., an earlier version or prior holder) that had the same name in a specified city.
-
E.
formerCapitalOf
Indicates that a place once served as the capital of another entity (such as a country or region) but no longer holds that status.
- F. None of above. chosen
Provenance (4 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_69e248fe1c2c8190ac914d2442ff3d26 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b27fc22c8190abda7398b9fb928c |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f1233300bc8190ac1639bdca1d7d99 |
completed | April 28, 2026, 9:14 p.m. |
Created at: April 17, 2026, 6:48 p.m.