Triple
T5109594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Deuteronomy |
E115181
|
entity |
| Predicate | fictionalUniverse |
P3758
|
FINISHED |
| Object | Cats (musical universe) |
E115051
|
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: Cats (musical universe) | Statement: [Old Deuteronomy, fictionalUniverse, Cats (musical universe)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cats (musical universe) Context triple: [Old Deuteronomy, fictionalUniverse, Cats (musical universe)]
-
A.
Cats (musical)
chosen
Cats (musical) is a long-running Andrew Lloyd Webber stage musical, based on T. S. Eliot’s whimsical poems, that tells the story of a tribe of cats through song and dance.
-
B.
Cat Country
Cat Country is a themed exhibit at the Memphis Zoo that showcases a variety of wild feline species in naturalistic habitats.
-
C.
Catz
Catz is the surname of Safra Catz, a prominent business executive best known as the CEO of Oracle Corporation.
-
D.
Catz
Catz is the informal nickname for St Catharine’s College, one of the constituent colleges of the University of Cambridge.
-
E.
Los Gatos
Los Gatos is an affluent town in California’s Silicon Valley known for its historic downtown, upscale residential neighborhoods, and proximity to major tech companies.
- 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_69bd4441d1648190a54a533895041987 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75ac19e88190aa8cc8b930a58d2d |
completed | March 20, 2026, 4:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bebaa322d08190911dd2ca91405c3c |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:41 p.m.