Triple
T3034994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aunt Polly |
E82986
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Phelps |
E82986
|
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: Phelps | Statement: [Aunt Polly, hasSurname, Phelps]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phelps Context triple: [Aunt Polly, hasSurname, Phelps]
-
A.
Phelps
chosen
Phelps is a surname that may refer to various individuals, including fictional characters such as Aunt Polly from classic literature.
-
B.
Michael Phelps
Michael Phelps is an American swimmer widely regarded as the most decorated Olympian of all time, known for his record-breaking medal haul and dominance in multiple Olympic Games.
-
C.
Jon Ledecky
Jon Ledecky is an American businessman and investor best known as a co-owner of the NHL’s New York Islanders.
-
D.
Mark Spitz
Mark Spitz is an American former competitive swimmer who became legendary for winning seven gold medals at the 1972 Munich Olympics, a record at the time.
-
E.
Bowerman
Bowerman is a surname most prominently associated with Bill Bowerman, the legendary American track coach and co-founder of Nike.
- 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_69ad8b21a62881908ec5dd4fba4a187c |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9b2a40b48190bfa7cdbb0fbd87f8 |
completed | March 8, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1eeeeff988190bb664c75d54d93d8 |
completed | March 11, 2026, 10:38 p.m. |
Created at: March 8, 2026, 3:01 p.m.