Triple
T3784743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camera Obscura de Tavira |
E85502
|
entity |
| Predicate | bestFor |
P18991
|
FINISHED |
| Object | city orientation |
—
|
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: city orientation | Statement: [Camera Obscura de Tavira, bestFor, city orientation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestFor Context triple: [Camera Obscura de Tavira, bestFor, city orientation]
-
A.
isSuitableFor
chosen
Indicates that one entity is appropriate, fitting, or well-matched for use, application, or association with another entity.
-
B.
bestOf
Indicates that one entity is the top-ranked or most outstanding member within a specified group, set, or collection.
-
C.
commendedFor
Indicates that one entity has expressed praise or approval toward another entity specifically because of a particular action, quality, or achievement.
-
D.
isDesignedFor
Indicates that one entity has been created, planned, or optimized specifically to serve the needs, purposes, or use of another entity.
-
E.
recommendedEquipment
Indicates that one entity suggests or endorses another entity as suitable equipment to be used in a particular context or activity.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
Created at: March 9, 2026, 3:13 p.m.