Triple
T17142750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanya Roberts |
E416010
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Blum |
E117700
|
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: Blum | Statement: [Tanya Roberts, familyName, Blum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Blum Context triple: [Tanya Roberts, familyName, Blum]
-
A.
Blum
chosen
Blum is a surname of German and Jewish origin borne by various notable individuals across fields such as mathematics, politics, and the arts.
-
B.
Bluhm
Bluhm is a surname most notably associated with Norman Bluhm, an American abstract expressionist painter.
-
C.
Blu
Blu is a popular electronic cigarette and vaping brand known for its range of rechargeable and disposable e-cigarette products.
-
D.
Blu
Blu is an American underground hip-hop rapper known for his introspective lyrics and acclaimed collaborations, particularly with producer Exile.
-
E.
Blu
Blu is a domesticated Spix's macaw who serves as the timid yet brave protagonist of the animated Rio film series.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f2d73c3c81908b875023bb925edb |
completed | April 18, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01415718c88190834fedae7b01ac69 |
completed | May 11, 2026, 2:39 a.m. |
Created at: April 10, 2026, 5:36 a.m.