Triple
T3287102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zorgons |
E69008
|
entity |
| Predicate | targetOfAttacks |
P860
|
FINISHED |
| Object | Danny |
E75485
|
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: Danny | Statement: [Zorgons, targetOfAttacks, Danny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Danny Context triple: [Zorgons, targetOfAttacks, Danny]
-
A.
Danny
chosen
Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
-
B.
Dave
Dave is a common masculine given name, often a shortened form of David, used widely in English-speaking countries.
-
C.
Dash
Dash is a lightweight, POSIX-compliant Unix shell designed for fast script execution and minimal resource usage, commonly used as the default /bin/sh on some Linux systems.
-
D.
Dash
Dash is an open-source Python framework for building interactive, web-based data visualization dashboards, particularly suited for analytical and scientific applications.
-
E.
Dash
Dash was a boutique clothing and accessories retail chain founded and operated by the Kardashian sisters, known for selling trendy, celebrity-inspired fashion.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb05779d08190a5517951e71b1380 |
completed | March 8, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e85f71508190b194b4d383d7ee32 |
completed | March 12, 2026, 4:22 p.m. |
Created at: March 8, 2026, 3:10 p.m.