Triple
T9998450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stan Lee |
E197263
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lieber |
E299637
|
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: Lieber | Statement: [Stan Lee, familyName, Lieber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lieber Context triple: [Stan Lee, familyName, Lieber]
-
A.
Lieber
chosen
Lieber is a surname of German origin borne by various notable individuals across fields such as science, politics, and the arts.
-
B.
Lieberher
Lieberher is the surname of American actor Jaeden Lieberher, known for his roles in films like "St. Vincent" and "It."
-
C.
Litzlitz
Litzlitz is a language of Vanuatu, also known as Naman, spoken by a small community on the island of Malakula.
-
D.
Lieben-Preis
Lieben-Preis is a prestigious Austrian scientific award, often compared to a regional Nobel Prize, granted for outstanding achievements in the fields of molecular biology, chemistry, and physics.
-
E.
Liebesbrand
Liebesbrand is a contemporary German novel by Feridun Zaimoglu that explores an intense, destructive love affair marked by obsession and emotional extremity.
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8c78448190a5332f4ff8a7b3dd |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d258439fe88190b17da69f542ecf61 |
completed | April 5, 2026, 12:40 p.m. |
Created at: March 30, 2026, 8:51 p.m.