Triple
T30020471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guangzhou–Foshan Metro Line |
E762721
|
entity |
| Predicate | integratesSystem |
P16507
|
FINISHED |
| Object | Guangzhou Metro |
—
|
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: Guangzhou Metro | Statement: [Guangzhou–Foshan Metro Line, integratesSystem, Guangzhou Metro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: integratesSystem Context triple: [Guangzhou–Foshan Metro Line, integratesSystem, Guangzhou Metro]
-
A.
integrates
Indicates that one entity combines or brings together another entity or set of entities into a unified, functioning whole.
-
B.
integratesService
chosen
Indicates that one entity connects with and enables the functionality of another service so they work together as a unified system.
-
C.
connectsSystem
Indicates that one system establishes a link or interface with another system, enabling interaction or data exchange between them.
-
D.
ecosystemIntegrationWith
Indicates how one entity is incorporated into, interacts with, or functions as part of another entity’s broader ecosystem of products, services, or systems.
-
E.
modelsSystemsWith
Indicates that one entity creates or uses a representation or abstraction to describe, analyze, or simulate another system.
- 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_69f2246ee6e48190b69e837b913b398a |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 29, 2026, 6:47 p.m.