Triple
T36162405
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baiyoke Tower II |
E1045912
|
entity |
| Predicate | hasViewingTime |
P125270
|
FINISHED |
| Object | daytime |
—
|
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: daytime | Statement: [Baiyoke Tower II, hasViewingTime, daytime]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewingTime Context triple: [Baiyoke Tower II, hasViewingTime, daytime]
-
A.
typicalViewingTime
Indicates the usual or most common amount of time an entity is viewed or watched under normal circumstances.
-
B.
minimumViewingTime
Indicates the least amount of time an item must be viewed or played for a condition (such as completion, eligibility, or credit) to be considered satisfied.
-
C.
viewedDuring
chosen
Indicates that one entity is being watched, observed, or visually experienced by another within a specified time period or event.
-
D.
hasRunningTimeCategory
Indicates that an entity is associated with a specific category based on its running time or duration.
-
E.
hasScreenTimeIn
Indicates that an entity appears on screen for a certain duration within a specified audiovisual work or segment.
- 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd5f29b1988190877764ef2a399c7f |
completed | May 8, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69fd5e30194c819085b5ce586122ab37 |
completed | May 8, 2026, 3:53 a.m. |
Created at: May 3, 2026, 4:08 p.m.