Triple
T34704440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agra–Jaipur route |
E1000461
|
entity |
| Predicate | linkIn |
P92534
|
FINISHED |
| Object | Golden Triangle tourist circuit |
—
|
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: Golden Triangle tourist circuit | Statement: [Agra–Jaipur route, linkIn, Golden Triangle tourist circuit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkIn Context triple: [Agra–Jaipur route, linkIn, Golden Triangle tourist circuit]
-
A.
linkedRight
Indicates that one entity is directly connected or positioned to the right of another entity in a sequence or structure.
-
B.
formsLinkIn
chosen
Indicates that one entity creates or establishes a connection or linkage within another entity or structure.
-
C.
linkType
Indicates the specific kind or category of relationship that connects two linked entities.
-
D.
linkedSite
Indicates that one site has an explicit hyperlink or reference connection to another site.
-
E.
textLinkedTo
Indicates that one piece of text is connected or associated with another, such as through a hyperlink, reference, or explicit textual relation.
- 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_69f76dab937881909c86f1b9ad50445f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f7805ce6208190ac6dbd9c97989978 |
completed | May 3, 2026, 5:05 p.m. |
| PD | Predicate disambiguation | batch_69f77956ec648190ba4fb7e9d83fd107 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.