Triple
T19872435
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 洛河 |
E477550
|
entity |
| Predicate | 与洛阳的关系 |
P107813
|
FINISHED |
| Object | 流经洛阳城北 |
—
|
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: 流经洛阳城北 | Statement: [洛河, 与洛阳的关系, 流经洛阳城北]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 与洛阳的关系 Context triple: [洛河, 与洛阳的关系, 流经洛阳城北]
-
A.
linkedToCapitalCity
Indicates a relationship where an entity is associated or connected to a capital city, typically as its relevant or corresponding urban center.
-
B.
relatesToAncientCity
chosen
Indicates a relationship or connection between an entity and an ancient city, such as origin, location, influence, or relevance.
-
C.
cityAssociatedWith
Indicates that there is a notable connection or relationship between a city and another entity, such as relevance, involvement, or contextual association.
-
D.
locatedInAncientCity
Indicates that an entity is situated within the boundaries or domain of an ancient city.
-
E.
linkedCity
Indicates that two entities are associated with each other through a specific city, such as being located in, connected via, or related by that city.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658d826f88190be04188997952d1b |
completed | April 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.