Triple
T11250000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Double Fine Productions |
E266299
|
entity |
| Predicate | developed |
P73
|
FINISHED |
| Object | Stacking |
E914203
|
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: Stacking | Statement: [Double Fine Productions, developed, Stacking]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stacking Context triple: [Double Fine Productions, developed, Stacking]
-
A.
Stacking
chosen
Stacking is a puzzle-adventure video game by Double Fine Productions centered on Russian nesting dolls, where players solve challenges by stacking into different characters to use their unique abilities.
-
B.
Stacked
Stacked is an American sitcom starring Pamela Anderson as a party girl who starts working in a bookstore, blending her comedic persona with a quirky workplace setting.
-
C.
Stacked Deck
"Stacked Deck" is a song featured on the album "Let's Roll."
-
D.
Operation Stack
Operation Stack was a traffic management system used in Kent, England, to queue freight traffic on the M20 motorway during disruptions to cross-Channel services.
-
E.
Stack
Stack is a cross-platform build tool and package manager for Haskell that simplifies project setup, dependency management, and reproducible builds.
- 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_69d6aac7953c8190b82caf9d7640fdf9 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e93212448190b46b3799b0bdfa0f |
completed | April 9, 2026, 6 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e4f40019588190864c59e8451e80bd |
completed | April 19, 2026, 3:25 p.m. |
Created at: April 8, 2026, 9:31 p.m.