Triple
T19918155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lauren Beukes |
E478717
|
entity |
| Predicate | awardReceivedFor |
P107
|
FINISHED |
| Object | Zoo City |
—
|
NE NERFINISHED |
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: Zoo City | Statement: [Lauren Beukes, awardReceivedFor, Zoo City]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zoo City Context triple: [Lauren Beukes, awardReceivedFor, Zoo City]
-
A.
Zoo City
chosen
Zoo City is a noir-infused urban fantasy novel by Lauren Beukes, set in an alternate Johannesburg where people magically manifest animal companions as a mark of their criminal guilt.
-
B.
The Zoo
"The Zoo" is a popular nickname for Kalamazoo, Michigan, reflecting the city's lively character and strong local identity.
-
C.
The Zoo
"The Zoo" is a popular hard rock song by the German band Scorpions, known for its heavy riff and frequent appearance in their live performances.
-
D.
The Zoo
The Zoo is the energetic student cheering section for the University of Montana Grizzlies football team, known for its loud, passionate game-day atmosphere.
-
E.
The Zoo
The Zoo is a Filipino rock band best known as one of the groups fronted by singer Arnel Pineda before he joined Journey.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c3d990819089386d9f30323e8c |
completed | April 20, 2026, 4:52 p.m. |
Created at: April 10, 2026, 1:53 p.m.