Triple
T33701321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Inspector Goole |
E863461
|
entity |
| Predicate | speaksFamousLine |
P84993
|
FINISHED |
| Object | We are members of one body. We are responsible for each other. |
—
|
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: We are members of one body. We are responsible for each other. | Statement: [Inspector Goole, speaksFamousLine, We are members of one body. We are responsible for each other.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: speaksFamousLine Context triple: [Inspector Goole, speaksFamousLine, We are members of one body. We are responsible for each other.]
-
A.
famousLineSpeaker
chosen
Indicates that the subject is the person who spoke or delivered the famous line referenced by the object.
-
B.
characterCatchphrase
Indicates that a particular phrase is commonly and distinctively used by a character as their catchphrase.
-
C.
isFamousExcerptOf
Indicates that one text passage is a well-known or widely recognized excerpt taken from a larger work.
-
D.
madeFamousByFilm
Indicates that something became widely known or gained significant public recognition as a result of being featured in a film.
-
E.
speaksInFilm
Indicates that a person or character provides spoken dialogue or voice work within a particular film.
- 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_69f3498723a08190ac034339cc78eade |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6ffbad8848190867c2988c0ceb84f |
completed | May 3, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69f6fc5740fc81909774a4f65201a3ff |
completed | May 3, 2026, 7:42 a.m. |
Created at: May 1, 2026, 1:43 a.m.