Triple
T20688907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mortal Kombat 11 |
E508496
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Kitana |
—
|
NE NERFINISHED |
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: Kitana | Statement: [Mortal Kombat 11, hasCharacter, Kitana]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitana Context triple: [Mortal Kombat 11, hasCharacter, Kitana]
-
A.
Kitana
chosen
Kitana is a prominent princess-assassin and fan-wielding fighter from the Mortal Kombat video game series, known for her agility, blue attire, and complex royal lineage.
-
B.
Pharah
Pharah is a rocket-launcher-wielding Egyptian security officer and aerial combat specialist from Blizzard’s hero shooter Overwatch.
-
C.
Blanka
Blanka is a given name used in various Slavic and Central European countries, equivalent to the name Blanca or Bianca.
-
D.
Sub-Zero
Sub-Zero is a popular Mortal Kombat fighter known for his ice-based powers, ninja appearance, and long-running rivalry with Scorpion.
-
E.
Katarina Taikon
Katarina Taikon was a prominent Swedish Romani activist and author, best known for her influential autobiographical "Katitzi" book series that highlighted Roma rights and experiences.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c1ed408190b72dd26b1e33f8a1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6c10b7b808190bdb8b08e53168fb8 |
completed | April 21, 2026, 12:12 a.m. |
Created at: April 16, 2026, 11:56 a.m.