Triple
T10816681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Hoyle |
E255247
|
entity |
| Predicate | theoryOpposed |
P95906
|
FINISHED |
| Object | Big Bang theory |
—
|
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: Big Bang theory | Statement: [Fred Hoyle, theoryOpposed, Big Bang theory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: theoryOpposed Context triple: [Fred Hoyle, theoryOpposed, Big Bang theory]
-
A.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
B.
typeOfOpposition
Indicates a relationship where one entity stands in opposition or contrast to another, such as being a rival, adversary, or countering force.
-
C.
positionOpposed
Indicates that two entities hold positions or stances that are in direct conflict or opposition to each other.
-
D.
opposedOutcome
Indicates that one entity’s outcome is in conflict with, counters, or works against the outcome associated with another entity.
-
E.
opposedQualityTo
Indicates that one quality stands in direct opposition or contrast to another quality.
- 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_69d6aa8081448190a9324184f2bd1c26 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733eea03c8190a68f4d4f89f497a2 |
completed | April 9, 2026, 5:06 a.m. |
| PD | Predicate disambiguation | batch_69d70d1bf3648190b36fa96ea018e0dc |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:18 p.m.