Triple
T21795542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’eggs |
E538083
|
entity |
| Predicate | hasSizeSystem |
P145679
|
FINISHED |
| Object | letter-based sizing |
—
|
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: letter-based sizing | Statement: [L’eggs, hasSizeSystem, letter-based sizing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSizeSystem Context triple: [L’eggs, hasSizeSystem, letter-based sizing]
-
A.
hasSize
Indicates that one entity possesses a particular physical magnitude or extent, such as length, volume, or overall dimensions.
-
B.
hasCatalogueSize
Indicates that an entity possesses a catalogue containing a specified number of items or entries.
-
C.
includesSizeRange
Indicates that one entity specifies or covers a particular range of sizes associated with another entity.
-
D.
hasRegulationSize
Indicates that something conforms to an officially defined or standard size specified by rules or regulations.
-
E.
hasTypicalMemberSize
Indicates the usual or characteristic size associated with members of a given class or group.
- 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f06223ecc48190bd3b173586ea7818 |
completed | April 28, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69e6c3a2898881909748935cf92f898c |
completed | April 21, 2026, 12:24 a.m. |
Created at: April 16, 2026, 6:53 p.m.