Triple
T29449327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tokeidai |
E746932
|
entity |
| Predicate | timekeepingFrequency |
P71998
|
FINISHED |
| Object | strikes every hour |
—
|
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: strikes every hour | Statement: [Tokeidai, timekeepingFrequency, strikes every hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timekeepingFrequency Context triple: [Tokeidai, timekeepingFrequency, strikes every hour]
-
A.
clockShowFrequency
chosen
Indicates how often a clock or time display is shown or updated within a given context.
-
B.
timekeepingAccuracy
Indicates how closely an entity’s measurement or tracking of time matches the true or standard reference time.
-
C.
measurementFrequency
Indicates how often a measurement is taken or recorded over time.
-
D.
timingStandard
Indicates that one entity specifies or conforms to the timing rules, constraints, or reference schedule defined by another entity.
-
E.
timeUnitOfFrequency
Indicates the unit of time (e.g., day, week, month) in which a given frequency is measured or expressed.
- 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_69f0a7a230488190b44a97fe3d16f731 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69f66b661648819084ef0f2cee9dbe45 |
completed | May 2, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69f66339175c819080bd70f0ff7057b1 |
completed | May 2, 2026, 8:48 p.m. |
Created at: April 28, 2026, 3:31 p.m.