Triple
T11430438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 10,000 metres at the 1948 Summer Olympics |
E270863
|
entity |
| Predicate | timingUnit |
P21771
|
FINISHED |
| Object | 1/10 second |
—
|
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: 1/10 second | Statement: [10,000 metres at the 1948 Summer Olympics, timingUnit, 1/10 second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timingUnit Context triple: [10,000 metres at the 1948 Summer Olympics, timingUnit, 1/10 second]
-
A.
timeUnitOfFrequency
Indicates the unit of time (e.g., day, week, month) in which a given frequency is measured or expressed.
-
B.
timeScaleUnit
Indicates the unit of temporal measurement (such as seconds, minutes, or hours) used to express a given time scale.
-
C.
timingStandard
Indicates that one entity specifies or conforms to the timing rules, constraints, or reference schedule defined by another entity.
-
D.
timingParameter
Indicates a relationship where one entity specifies or controls a temporal setting, constraint, or configuration parameter that determines the timing behavior of another entity or process.
-
E.
timingMethod
chosen
Indicates the method or technique used to measure or record the timing of an event or process.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c1bfb881909720c74fe0fa837f |
completed | April 9, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:35 p.m.