Triple
T4622883
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Stooges |
E101027
|
entity |
| Predicate | numberOfShortsForColumbia |
P57485
|
FINISHED |
| Object | 190 |
—
|
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: 190 | Statement: [Three Stooges, numberOfShortsForColumbia, 190]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfShortsForColumbia Context triple: [Three Stooges, numberOfShortsForColumbia, 190]
-
A.
isShort
Indicates that one entity has a relatively small height, length, or duration compared to a standard or to other entities.
-
B.
typicalRuntimePerShort
Indicates the usual or average amount of time it takes to complete a short instance of the referenced activity or process.
-
C.
hasApproximateNumberOfMiniatures
Indicates that an entity is associated with an estimated or non-exact count of miniatures.
-
D.
numberOfCapsules
Indicates the quantity or count of capsules associated with an entity or event.
-
E.
numberOfRivets
Indicates the quantitative relationship specifying how many rivets are associated with a given object or structure.
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a053d38819097b3ecbc06aa6e4d |
completed | March 20, 2026, 2:30 p.m. |
| PD | Predicate disambiguation | batch_69bd5231db7c8190b38d4fdbad8bf842 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:12 p.m.