Triple
T37339884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honey, We Shrunk Ourselves |
E927001
|
entity |
| Predicate | hasFullSizedCharacters |
P187746
|
FINISHED |
| Object | children |
—
|
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: children | Statement: [Honey, We Shrunk Ourselves, hasFullSizedCharacters, children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFullSizedCharacters Context triple: [Honey, We Shrunk Ourselves, hasFullSizedCharacters, children]
-
A.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
-
B.
hasMediumCharacter
Indicates that one entity possesses or is associated with a character whose size, intensity, or degree is classified as medium.
-
C.
hasCharacterSetSizeCategory
Indicates the relationship between something and the category that classifies the size of its character set.
-
D.
hasNumberOfBasicCharacters
Indicates the quantity of basic (non-accented or fundamental) characters associated with an entity.
-
E.
hasGlyphRepertoireSize
Indicates the number of distinct glyphs included in an entity’s glyph repertoire.
- 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_69f76eb4e8a881908bd40da28f36fc7e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb8c38a9688190be524246f5682107 |
completed | May 6, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9c6e0481908565bd849e869b24 |
completed | May 6, 2026, 3:13 p.m. |
| PDg | Predicate description generation | batch_69fb8c37931c81909da038c18ed9add2 |
completed | May 6, 2026, 6:45 p.m. |
Created at: May 3, 2026, 4:16 p.m.