Triple
T12677498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince John of Lancaster |
E302853
|
entity |
| Predicate | roleInShakespeare |
P44516
|
FINISHED |
| Object | son of King Henry IV |
—
|
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: son of King Henry IV | Statement: [Prince John of Lancaster, roleInShakespeare, son of King Henry IV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInShakespeare Context triple: [Prince John of Lancaster, roleInShakespeare, son of King Henry IV]
-
A.
roleInFamousPlay
Indicates that an entity portrays or has portrayed a specific character in a well-known theatrical play.
-
B.
roleInRomeoAndJuliet
Indicates the specific character or part that an entity plays in the work "Romeo and Juliet."
-
C.
theaterRole
chosen
Indicates that an entity holds or performs a specific role or character in a theatrical production in relation to another entity (such as a play or performance).
-
D.
roleInFalstaffArc
Indicates the specific function or contribution an entity has within the narrative or developmental arc associated with Falstaff.
-
E.
roleInRhyme
Indicates the specific function or part an entity plays within a rhyme, such as a character, object, or structural element of the rhyming text.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961b0d9c88190a05d6cbcb7a1642d |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960bb64ec8190bd0400cf0cc8b0a7 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:20 p.m.