Triple
T5746861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judy Garland |
E126754
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Gumm |
E21962
|
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: Gumm | Statement: [Judy Garland, familyName, Gumm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gumm Context triple: [Judy Garland, familyName, Gumm]
-
A.
Gumm
chosen
Gumm is the birth surname of American actress and singer Judy Garland, originally Frances Ethel Gumm.
-
B.
Goo
Goo is an energetic, talkative girl from the animated series "Foster's Home for Imaginary Friends" known for her overactive imagination and rapid-fire speech.
-
C.
Goo
Goo is a 1990 alternative rock album by Sonic Youth, noted for its noisy guitar sound and influential role in bringing underground rock toward the mainstream.
-
D.
Gooigi
Gooigi is a green, goo-like doppelgänger of Luigi from the Luigi’s Mansion series, used as a playable helper character to solve puzzles and reach otherwise inaccessible areas.
-
E.
Goop
Goop is a lifestyle and wellness brand known for its high-end products, health advice, and often controversial alternative medicine recommendations.
- 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_69c0083179548190b384b0bf3c08ca4d |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02885b0288190835809681a364b1f |
completed | March 22, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097f9b6e08190bb68ea850ba813ff |
completed | March 23, 2026, 1:31 a.m. |
Created at: March 22, 2026, 3:48 p.m.