Triple
T9264278
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DOOMS |
E222656
|
entity |
| Predicate | higherLevelEffect |
P87861
|
FINISHED |
| Object | stronger connection to the Beach |
—
|
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: stronger connection to the Beach | Statement: [DOOMS, higherLevelEffect, stronger connection to the Beach]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: higherLevelEffect Context triple: [DOOMS, higherLevelEffect, stronger connection to the Beach]
-
A.
tierEffect
Indicates how belonging to a particular tier influences or modifies the outcome, behavior, or properties associated with that tier.
-
B.
predictedEffect
Indicates that one entity is expected to cause, influence, or result in a particular outcome or consequence for another entity.
-
C.
affectedLevel
Indicates the degree or extent to which one entity is impacted or influenced by another entity or event.
-
D.
primaryEffect
Indicates the main direct outcome or consequence that results from a given cause, action, or condition.
-
E.
effectOnOthers
Indicates the impact or influence that one entity’s actions, presence, or state has on other entities.
- 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_69ca841f2e808190a64f4c31903a1332 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd0748a1f481909d9d876692cefccc |
completed | April 1, 2026, 11:53 a.m. |
| PD | Predicate disambiguation | batch_69cc7a537bbc8190baee71f556e52a7b |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc95597be081908ece2491dd2f0f74 |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:32 p.m.