Triple
T30832999
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Picket Fences |
E785273
|
entity |
| Predicate | hasLegalDramaElements |
P21484
|
FINISHED |
| Object | Yes |
—
|
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: Yes | Statement: [Picket Fences, hasLegalDramaElements, Yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalDramaElements Context triple: [Picket Fences, hasLegalDramaElements, Yes]
-
A.
hasDramaticElements
chosen
Indicates that something contains features or qualities characteristic of drama, such as heightened emotion, tension, or conflict.
-
B.
hasLegalIssue
Indicates that an entity is involved in, associated with, or subject to a legal problem, dispute, or proceeding.
-
C.
hasLegalAndPoliticalElements
Indicates that a situation, issue, or relationship involves both legal aspects (laws, regulations, rights) and political aspects (power, governance, policy decisions) at the same time.
-
D.
hasLegalSubject
Indicates that an entity serves as the legal subject (e.g., rights-holder or obligated party) in a legal relationship or context.
-
E.
hasLegalRelevanceIn
Indicates that something is legally significant, applicable, or has consequences within a specified legal context, case, or jurisdiction.
- 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_69f224b73d8c81908129383bfb397c87 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fcf1b3d9a08190850b388308656266 |
completed | May 7, 2026, 8:10 p.m. |
| PD | Predicate disambiguation | batch_69fcf0226d8c8190b23dceafb1794995 |
completed | May 7, 2026, 8:03 p.m. |
Created at: April 29, 2026, 8:44 p.m.