Triple
T7119543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tianjin Eye |
E165912
|
entity |
| Predicate | offersViewType |
P3821
|
FINISHED |
| Object | panoramic views |
—
|
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: panoramic views | Statement: [Tianjin Eye, offersViewType, panoramic views]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersViewType Context triple: [Tianjin Eye, offersViewType, panoramic views]
-
A.
offersPanelType
Indicates that an entity provides or makes available a specific type of panel as part of its offerings.
-
B.
offersViewOf
chosen
Indicates that one entity provides a vantage point from which another entity can be seen or visually appreciated.
-
C.
offersPlanType
Indicates that one entity provides or makes available a specific type of plan to another entity or in a given context.
-
D.
offersServiceType
Indicates that one entity provides or makes available a specific type or category of service to another entity or the public.
-
E.
offersObject
Indicates that a subject provides or makes available a specific object to another party as an offer.
- 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_69c6888227bc8190a1394679e3116f90 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e61b8a288190a165ea25adfaaef5 |
completed | March 27, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69c6e1c4f9788190830288d00cc37026 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:43 p.m.