Triple
T28896454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ecco |
E732845
|
entity |
| Predicate | hasCompanionCharacters |
P189712
|
FINISHED |
| Object | other dolphins |
—
|
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: other dolphins | Statement: [Ecco, hasCompanionCharacters, other dolphins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCompanionCharacters Context triple: [Ecco, hasCompanionCharacters, other dolphins]
-
A.
hasFictionalCompanion
chosen
Indicates that one entity has another entity as its fictional companion, typically within a narrative or imaginative context.
-
B.
hasNumberOfCompanions
Indicates the quantity of companions or associates that an entity has.
-
C.
hasHumanPartnerCharacter
Indicates that an entity is associated with a partner character who is human.
-
D.
hasSiblingProtagonists
Indicates that the work features two or more protagonists who are siblings to each other.
-
E.
wasCompanionOf
Indicates that one entity accompanied or associated closely with another, typically as a partner, ally, or fellow participant over some period of time.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_6a000014497c819088d5cda3977522dd |
completed | May 10, 2026, 3:48 a.m. |
| PD | Predicate disambiguation | batch_69ffff9a52b08190be1024e0fb6fe661 |
completed | May 10, 2026, 3:46 a.m. |
Created at: April 28, 2026, 7:59 a.m.