Triple
T36332018
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HHA: SP |
E894674
|
entity |
| Predicate | networkLineType |
P15027
|
FINISHED |
| Object | metro |
—
|
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: metro | Statement: [HHA: SP, networkLineType, metro]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: networkLineType Context triple: [HHA: SP, networkLineType, metro]
-
A.
networkLine
Indicates that there is a connection or linkage between entities within a network structure or system.
-
B.
lineType
chosen
Indicates the specific category or style of a line used in a representation, such as its function or visual convention.
-
C.
networkType
Indicates the category or kind of network associated with or used by an entity (e.g., wired, wireless, virtual, or specific protocol-based networks).
-
D.
networkColorOfLine
Indicates the color assigned to a specific line within a network (such as a transit or communication network).
-
E.
trailNetworkType
Indicates the classification of a trail within a broader trail network, such as its role, category, or type of route in that 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_69f76e4dcf088190a6c3216c209cab52 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c777e924819081a6634f549fe552 |
completed | May 3, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69f7c475c58c8190a883554231e88c88 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:09 p.m.