Triple
T2778456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ode on the Death of a Favourite Cat, Drowned in a Tub of Gold Fishes |
E61633
|
entity |
| Predicate | linesPerStanza |
P27487
|
FINISHED |
| Object | 6 |
—
|
LITERAL 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: 6 | Statement: [Ode on the Death of a Favourite Cat, Drowned in a Tub of Gold Fishes, linesPerStanza, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linesPerStanza Context triple: [Ode on the Death of a Favourite Cat, Drowned in a Tub of Gold Fishes, linesPerStanza, 6]
-
A.
lineCountPerStanza
chosen
Indicates the number of lines contained in each stanza of a poem or song.
-
B.
numberOfStanzasInOriginalPoem
Indicates the total count of stanzas contained in the poem’s original version.
-
C.
numberOfOfficialStanzas
Indicates the total count of officially recognized stanzas associated with an entity, such as a song, poem, or anthem.
-
D.
numberOfSonnets
Indicates the quantity of sonnets associated with a given entity.
-
E.
numberOfCantos
Indicates the total count of cantos associated with a given work or entity.
- F. None of above.
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_69ab4b7e43c48190997b8fc8fb1663ab |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdd00b65c8190a8ea444308c4fa2b |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.