Triple
T27623841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mehndi ceremony |
E696146
|
entity |
| Predicate | hasTemporalDuration |
P154713
|
FINISHED |
| Object | several hours |
—
|
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: several hours | Statement: [Mehndi ceremony, hasTemporalDuration, several hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporalDuration Context triple: [Mehndi ceremony, hasTemporalDuration, several hours]
-
A.
hasDurationType
Indicates that something is associated with a specific kind or category of duration (e.g., temporary, permanent, short-term, long-term).
-
B.
hasDurationCharacteristic
chosen
Indicates that something possesses a specific temporal property, such as length, span, or persistence over time.
-
C.
hasTemporalAttribute
Indicates that an entity is associated with a specific temporal property or characteristic, such as time, duration, or period.
-
D.
hasTemporalEnd
Indicates that an event, state, or process concludes or terminates at a specific point or interval in time.
-
E.
hasTemporalResolution
Indicates that one entity specifies the level of temporal detail or granularity at which another entity’s data, observation, or process is measured or represented.
- 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_69ef59092c8881908114ad184248cc46 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 27, 2026, 2:16 p.m.