Triple
T32443527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butterfeld |
E829078
|
entity |
| Predicate | hasNotableSinglePrimaryMeaning |
P100885
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [Butterfeld, hasNotableSinglePrimaryMeaning, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSinglePrimaryMeaning Context triple: [Butterfeld, hasNotableSinglePrimaryMeaning, false]
-
A.
hasMultipleMeanings
chosen
Indicates that a term, symbol, or expression is associated with more than one distinct meaning or interpretation.
-
B.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
C.
possibleMeaning
Indicates that something may plausibly represent, signify, or be interpreted as a particular meaning or sense.
-
D.
commonMeaning
Indicates that multiple entities share the same or very similar meaning or semantic interpretation.
-
E.
hasMeaningCategory
Indicates that something is associated with a particular category of meaning or semantic type.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a012594c27081908c80f0e0e6010290 |
completed | May 11, 2026, 12:40 a.m. |
| PD | Predicate disambiguation | batch_6a01252350548190b1df9edc9e581e91 |
completed | May 11, 2026, 12:38 a.m. |
Created at: May 1, 2026, 12:55 a.m.