Triple
T14507053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pam / Cassidy |
E340290
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Cassidy |
E648751
|
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: Cassidy | Statement: [Pam / Cassidy, alsoKnownAs, Cassidy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cassidy Context triple: [Pam / Cassidy, alsoKnownAs, Cassidy]
-
A.
Cassidy
"Cassidy" is a beloved Grateful Dead–associated song by Bob Weir, known for its intricate lyrics and fusion of folk, rock, and improvisational elements.
-
B.
Cassidy
Cassidy is an American rapper known for his punchline-heavy battle rap style and early-2000s hits like "Hotel" and "I'm a Hustla."
-
C.
Cassidy
chosen
Cassidy is a feminine given name of Irish origin that has become popular in English-speaking countries.
-
D.
Cassidy
"Cassidy" is a 1970s American television movie (and short-lived series pilot) starring Angie Dickinson as a politically ambitious country singer.
-
E.
Cassidy
Cassidy is a surname most famously associated with American singer Eva Cassidy, known for her emotive interpretations of jazz, blues, folk, and pop standards.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e40e44819084f323f8f9982b75 |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6da07ff481909fb2463b0ea92849 |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 10, 2026, 1:21 a.m.