Triple
T719664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clancy Brown |
E14387
|
entity |
| Predicate | voiceWork |
P18510
|
FINISHED |
| Object | Mr. Krabs in SpongeBob SquarePants franchise |
—
|
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: Mr. Krabs in SpongeBob SquarePants franchise | Statement: [Clancy Brown, voiceWork, Mr. Krabs in SpongeBob SquarePants franchise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: voiceWork Context triple: [Clancy Brown, voiceWork, Mr. Krabs in SpongeBob SquarePants franchise]
-
A.
alsoSpeak
Indicates that an entity, in addition to another language or mode of communication already mentioned, speaks this additional language or communicates in this additional way.
-
B.
voiceType
Indicates the specific vocal style, quality, or role associated with an entity’s voice in a given context.
-
C.
hasSpeech
Indicates that an entity produces, delivers, or is associated with a spoken utterance or verbal expression.
-
D.
narratedTo
Indicates that one entity tells or recounts a story, event, or information directly to another entity as the audience.
-
E.
speechRegister
Indicates the level or style of formality in speech that one entity uses when addressing another.
- F. None of above. chosen
Provenance (4 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_69a4934a36e081909e7abef98b898a4e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a58e65e8819098cba7e6a20d8f33 |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f513608190b716b939d574c292 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.