Triple
T14086019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Orphant Annie |
E338997
|
entity |
| Predicate | hasLineCountApprox |
P89489
|
FINISHED |
| Object | over 100 lines |
—
|
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: over 100 lines | Statement: [Little Orphant Annie, hasLineCountApprox, over 100 lines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLineCountApprox Context triple: [Little Orphant Annie, hasLineCountApprox, over 100 lines]
-
A.
hasApproximateLineCount
chosen
Indicates that one entity is associated with an estimated or non-exact number of lines represented by the other entity.
-
B.
hasNumberOfLines
Indicates the relationship that specifies how many lines are associated with a given entity.
-
C.
hasLineLength
Indicates that one entity has, is characterized by, or is associated with a specific line length value.
-
D.
hasPageCountApprox
Indicates that an entity is associated with an approximate or estimated number of pages, rather than an exact page count.
-
E.
hasApproximateNumberOfColumns
Indicates that an entity is associated with an estimated or non-exact count of columns.
- 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_69d81c687b0c819087fd9ed4198403f8 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5edff1b881909ea56dc2429ef2dd |
completed | April 14, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69de05b0e6c88190a819eeba0028981f |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.