Triple
T27992924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matteo Ricci |
E706927
|
entity |
| Predicate | laterBasedInNanjing |
P18745
|
FINISHED |
| Object | 1598 |
—
|
LITERAL 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: 1598 | Statement: [Matteo Ricci, laterBasedInNanjing, 1598]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterBasedInNanjing Context triple: [Matteo Ricci, laterBasedInNanjing, 1598]
-
A.
basedInLater
Indicates that an entity is located or headquartered in a place during a later time period or phase, relative to some earlier location or state.
-
B.
laterLivedIn
chosen
Indicates that one entity resided in a particular place during a later period of its life, after an earlier residence elsewhere.
-
C.
basedInCity
Indicates that an entity has its primary location, headquarters, or main operations situated in a specified city.
-
D.
locatedInOldCity
Indicates that an entity is situated within the boundaries of an old or historic part of a city.
-
E.
historicallyBasedIn
Indicates that one entity is located in or associated with a place as its base of operations during a specific historical period.
- F. None of above.
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_69ef96b980d88190a753b2f9a978595a |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: April 27, 2026, 7:51 p.m.