Triple
T11899321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Magic Wand |
E283109
|
entity |
| Predicate | album |
P1995
|
FINISHED |
| Object | IGOR |
E283100
|
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: IGOR | Statement: [New Magic Wand, album, IGOR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IGOR Context triple: [New Magic Wand, album, IGOR]
-
A.
Igor
Igor is a masculine given name of Russian origin, widely used in Slavic countries and beyond.
-
B.
Igor
chosen
Igor is Tyler, the Creator’s critically acclaimed 2019 studio album that blends hip hop, R&B, and neo-soul into a concept-driven exploration of love and heartbreak.
-
C.
Igny
Igny is a commune in the southern suburbs of Paris, located in the Essonne department in Île-de-France, France.
-
D.
Gorogoa
Gorogoa is a hand-illustrated, narrative puzzle video game known for its innovative panel-manipulation mechanics and seamless, story-driven visual design.
-
E.
Chigorodó
Chigorodó is a municipality in Colombia’s Antioquia Department, known for its agricultural production and location in the Urabá region.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd13cc10819089d8d5103e562924 |
completed | April 10, 2026, 11:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a5753848190b0ab7da327c9aa22 |
completed | May 2, 2026, 2:29 p.m. |
Created at: April 8, 2026, 9:44 p.m.