Triple
T30889994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Children's and Household Tales |
E786872
|
entity |
| Predicate | finalEditionStoryCount |
P194471
|
FINISHED |
| Object | 210 |
—
|
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: 210 | Statement: [Children's and Household Tales, finalEditionStoryCount, 210]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: finalEditionStoryCount Context triple: [Children's and Household Tales, finalEditionStoryCount, 210]
-
A.
numberOfStories
Indicates the total count of levels or floors that a structure or building has.
-
B.
finalIssueNumber
Indicates the issue number assigned to the last or concluding installment in a series or publication run.
-
C.
mainSeriesIssueCount
Indicates the total number of issues contained in the primary or main series associated with an entity.
-
D.
numberOfEditions
Indicates the total count of distinct editions associated with a given entity.
-
E.
numberOfEmbeddedStories
Indicates the count of stories that are embedded within a given item or context.
- 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_69f224bbfa7c81908448e0c261c523e3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69fd76d0d7608190b350336d6c18182d |
completed | May 8, 2026, 5:38 a.m. |
Created at: April 29, 2026, 8:49 p.m.