Triple
T13829181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Red Machine |
E332337
|
entity |
| Predicate | notableSong |
P4
|
FINISHED |
| Object | Phoenix |
E496332
|
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: Phoenix | Statement: [Big Red Machine, notableSong, Phoenix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phoenix Context triple: [Big Red Machine, notableSong, Phoenix]
-
A.
Phoenix
Phoenix is the capital and largest city of the U.S. state of Arizona, known for its desert climate, rapid growth, and role as a major economic and cultural center in the American Southwest.
-
B.
Phoenix
Phoenix is the mythical bird that cyclically regenerates from its own ashes, symbolizing rebirth and renewal.
-
C.
Phoenix
chosen
Phoenix is a French indie pop and rock band known for their catchy, synth-infused sound and critically acclaimed albums like "Wolfgang Amadeus Phoenix."
-
D.
Phoenix
Phoenix is a high-performance web development framework for the Elixir programming language, designed for building scalable, real-time applications.
-
E.
Phoenix
Phoenix is the powerful mutant alter-ego of Jean Grey in the X-Men franchise, known for her immense telepathic and telekinetic abilities and central role in several major storylines.
- 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_69d81c5ae7c88190b0dd41bdafeb5999 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02970df88190a1bf35dffd131d9d |
completed | April 14, 2026, 9:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1af38248190a85d0fa3a26c3d08 |
completed | May 6, 2026, 8:16 p.m. |
Created at: April 9, 2026, 10:13 p.m.