Triple
T5070815
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvia Earle |
E114272
|
entity |
| Predicate | spokenText |
P35243
|
FINISHED |
| Object | “No water, no life. No blue, no green.” |
—
|
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: “No water, no life. No blue, no green.” | Statement: [Sylvia Earle, spokenText, “No water, no life. No blue, no green.”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenText Context triple: [Sylvia Earle, spokenText, “No water, no life. No blue, no green.”]
-
A.
spokenAlong
Indicates that two or more languages are used concurrently or within the same context in a particular place, time, or situation.
-
B.
speechContent
chosen
Indicates that one entity expresses, conveys, or contains the spoken or written content associated with another entity’s act of speaking or communication.
-
C.
speechType
Indicates the specific category or form of spoken or written communication that an utterance or speech act belongs to (e.g., question, statement, command).
-
D.
spokenNear
Indicates that one entity spoke in close physical proximity to another entity or location.
-
E.
spokenOn
Indicates that an utterance or speech act occurred at or during a specific time or date.
- 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_69bd443cf28c8190ad371d603563dbdd |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74a0aa048190ba01281f1b160609 |
completed | March 20, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69bd7157fe608190b4515d56fdd0a616 |
completed | March 20, 2026, 4:10 p.m. |
Created at: March 20, 2026, 1:39 p.m.