Triple
T20359921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cats (franchise) |
E496748
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Growltiger |
—
|
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: Growltiger | Statement: [Cats (franchise), hasCharacter, Growltiger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Growltiger Context triple: [Cats (franchise), hasCharacter, Growltiger]
-
A.
Growltiger
chosen
Growltiger is a fictional pirate cat character from T. S. Eliot’s *Old Possum's Book of Practical Cats*, later featured in Andrew Lloyd Webber’s musical *Cats*.
-
B.
Basilisk
The Basilisk is a gigantic, deadly serpent from the Harry Potter series whose gaze can kill and whose venom is among the most lethal magical substances.
-
C.
panther Bagheera
Panther Bagheera is the wise and protective black panther who mentors and safeguards Mowgli in Rudyard Kipling’s "The Jungle Book."
-
D.
King Kobra
King Kobra is an American hard rock and glam metal band formed in the 1980s, known for its melodic hooks and association with prominent acts in the Los Angeles metal scene.
-
E.
Tigery
Tigery is a small commune in the Essonne department of the Île-de-France region in northern France.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678584294819093788ccf2fb8e588 |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:25 a.m.