Triple
T15388455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing central axis |
E367973
|
entity |
| Predicate | containsViewCorridor |
P5520
|
FINISHED |
| Object | sightline through Tiananmen and Forbidden City |
—
|
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: sightline through Tiananmen and Forbidden City | Statement: [Beijing central axis, containsViewCorridor, sightline through Tiananmen and Forbidden City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsViewCorridor Context triple: [Beijing central axis, containsViewCorridor, sightline through Tiananmen and Forbidden City]
-
A.
hasCorridor
chosen
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
B.
onCorridorBetween
Indicates that one entity is located along the corridor that lies between two other reference entities or areas.
-
C.
isStopOnCorridor
Indicates that a location functions as a designated stop situated along a corridor or route.
-
D.
isPartOfCorridorSystem
Indicates that one entity forms a component or segment within a larger interconnected corridor system.
-
E.
hasServiceOnCorridor
Indicates that a service operates along, or is provided on, a specific corridor or route.
- 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_69d85a1551a08190ba2caea7cd51c639 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e761b688190893a81246b735b76 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27742a881909cd73cc5c7d062fd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:19 a.m.