Triple
T3113783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jesse Eisenberg |
E65009
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Adventureland |
E46596
|
NE 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: Adventureland | Statement: [Jesse Eisenberg, notableWork, Adventureland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Adventureland Context triple: [Jesse Eisenberg, notableWork, Adventureland]
-
A.
Adventureland
chosen
Adventureland is a themed land found in several Disney parks, designed to evoke exotic, tropical locales through attractions, lush landscaping, and immersive storytelling.
-
B.
Discoveryland
Discoveryland is a retro-futuristic themed land at Disneyland Paris inspired by the visionary works of Jules Verne and classic science fiction.
-
C.
The Island of Adventure
The Island of Adventure is a children's adventure novel by Enid Blyton that follows a group of children uncovering mysteries and dangers on a remote, rugged island.
-
D.
Fantasyland Station
Fantasyland Station is a themed stop on the Walt Disney World Railroad in Magic Kingdom, serving guests traveling to and from the park’s Fantasyland area.
-
E.
Fantasyland
Fantasyland is a themed area in Disney parks that brings classic fairy tales and animated stories to life through rides, attractions, and immersive environments.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ad857fcc088190b0c4d45a5cde6f61 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada43c79448190aa72f707319e8c5e |
completed | March 8, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2039b11d4819095ee77d84d6e7b8a |
completed | March 12, 2026, 12:06 a.m. |
Created at: March 8, 2026, 3:04 p.m.