Triple
T1200125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andy Hardy film series |
E25759
|
entity |
| Predicate | typicalRuntimeRange |
P25501
|
FINISHED |
| Object | feature-length |
—
|
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: feature-length | Statement: [Andy Hardy film series, typicalRuntimeRange, feature-length]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRuntimeRange Context triple: [Andy Hardy film series, typicalRuntimeRange, feature-length]
-
A.
typicalRange
Indicates the usual or expected range of values, conditions, or states within which something normally occurs or applies.
-
B.
typicalEnergyRange
Indicates the usual or characteristic range of energy values associated with an entity, process, or interaction.
-
C.
typicalDurationDays
Indicates the usual or expected number of days that an associated event, process, or state typically lasts.
-
D.
runtimeMinutes
Indicates the total duration of something, typically a media work or process, measured in minutes.
-
E.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
- F. None of above. chosen
Provenance (4 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_69a49429f5ec8190a6a205eb0ae81e5e |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd9ec3488190afe35af54efae5e9 |
completed | March 1, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69a4bb5ed2b88190aab992913957e1cf |
completed | March 1, 2026, 10:19 p.m. |
| PDg | Predicate description generation | batch_69a4bcc82e38819081c3615e1cc7a66f |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:46 p.m.