Triple
T15048670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Button Gwinnett |
E379296
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Button |
E856529
|
NE 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: Button | Statement: [Button Gwinnett, givenName, Button]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Button Context triple: [Button Gwinnett, givenName, Button]
-
A.
Button
chosen
Button is a common English surname borne by various real and fictional individuals, including the character Benjamin Button.
-
B.
Buttons
"Buttons" is a notable creative work by Sean Garrett, recognized as a key contribution to his career.
-
C.
Button, Button
"Button, Button" is a suspenseful short story by Richard Matheson that explores moral dilemmas and the consequences of greed through a mysterious offer involving a deadly button.
-
D.
MatButton
MatButton is the Angular Material component that provides a styled, accessible button implementation consistent with the Material Design specification.
-
E.
BTN
BTN is the three-letter ISO 3166-1 alpha-3 country code assigned to Bhutan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69deda8e64e48190873104a02a676ff3 |
completed | April 15, 2026, 12:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9de83b648190ba437c0fac164ec6 |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 3 a.m.