Triple
T16779511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ariel |
E407819
|
entity |
| Predicate | hasRelationshipWith |
P2830
|
FINISHED |
| Object | Tupolski |
E410737
|
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: Tupolski | Statement: [Ariel, hasRelationshipWith, Tupolski]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tupolski Context triple: [Ariel, hasRelationshipWith, Tupolski]
-
A.
Tupolski
chosen
Tupolski is a hard-edged, morally ambiguous police detective in Martin McDonagh’s dark play "The Pillowman," known for his interrogations and psychological manipulation.
-
B.
Turchynov
Turchynov is a Ukrainian politician and former acting president of Ukraine known for his roles in the country’s post-2014 political transition.
-
C.
Tupikov
Tupikov is a Russian surname most notably associated with Vasiliy Tupikov, a Soviet military figure.
-
D.
Totleben
Totleben is a German-origin surname most notably associated with Eduard Totleben, a prominent 19th-century Russian military engineer and general.
-
E.
Tolbukhin
Tolbukhin is a Russian surname most notably associated with Soviet military commander Fyodor Tolbukhin, a prominent general during World War II.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b21401b881909bbbc7382e851a90 |
completed | April 18, 2026, 4:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00ab00cf708190a2562fa14d72a4df |
completed | May 10, 2026, 3:57 p.m. |
Created at: April 10, 2026, 5:22 a.m.