Triple
T4005353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayelet Zurer |
E89512
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Zurer
Zurer is the surname of Ayelet Zurer, an Israeli actress known for her roles in international films and television series.
|
E407474
|
NE FINISHED |
How this triple was built (4 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: Zurer | Statement: [Ayelet Zurer, familyName, Zurer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zurer Context triple: [Ayelet Zurer, familyName, Zurer]
-
A.
Zülicke
Zülicke is a German surname most notably associated with individuals such as physicist Lutz Zülicke.
-
B.
Zau
Zau is an ancient city, historically known as Sais, that served as an important religious and political center in Egypt’s Nile Delta.
-
C.
Kritzinger
Kritzinger is a German surname most notably associated with Friedrich Wilhelm Kritzinger, a high-ranking Nazi official involved in the administrative planning of the Holocaust.
-
D.
Zurbriggen
Zurbriggen is a Swiss surname notably associated with mountaineers and alpine skiers.
-
E.
Zierer
Zierer is a German amusement ride manufacturer known for producing family-friendly roller coasters and classic flat rides for theme parks worldwide.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zurer Triple: [Ayelet Zurer, familyName, Zurer]
Generated description
Zurer is the surname of Ayelet Zurer, an Israeli actress known for her roles in international films and television series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zurer Target entity description: Zurer is the surname of Ayelet Zurer, an Israeli actress known for her roles in international films and television series.
-
A.
Zülicke
Zülicke is a German surname most notably associated with individuals such as physicist Lutz Zülicke.
-
B.
Zau
Zau is an ancient city, historically known as Sais, that served as an important religious and political center in Egypt’s Nile Delta.
-
C.
Kritzinger
Kritzinger is a German surname most notably associated with Friedrich Wilhelm Kritzinger, a high-ranking Nazi official involved in the administrative planning of the Holocaust.
-
D.
Zurbriggen
Zurbriggen is a Swiss surname notably associated with mountaineers and alpine skiers.
-
E.
Zierer
Zierer is a German amusement ride manufacturer known for producing family-friendly roller coasters and classic flat rides for theme parks worldwide.
- F. None of above. chosen
Provenance (5 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_69aed9585e788190bec2d39deba3750f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa5f7b308190adaad864eec98936 |
completed | March 9, 2026, 4:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b54c648d3c8190a85e5cdfb20f6044 |
completed | March 14, 2026, 11:54 a.m. |
| NEDg | Description generation | batch_69b54cf3da208190aa844c9ea66354fe |
completed | March 14, 2026, 11:56 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b55159dc288190a63d5f5164b73bbb |
completed | March 14, 2026, 12:15 p.m. |
Created at: March 9, 2026, 3:34 p.m.