Triple
T22494337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jaroslav Pelikan |
E556099
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Pelikan
Pelikan is a surname of Slavic origin borne by various notable individuals, including scholars and public figures.
|
E1540499
|
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: Pelikan | Statement: [Jaroslav Pelikan, familyName, Pelikan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pelikan Context triple: [Jaroslav Pelikan, familyName, Pelikan]
-
A.
Magura
Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
-
B.
Magura
Magura is a mountain peak in the Kysucké Beskydy range of northern Slovakia, known for its forested slopes and scenic hiking routes.
-
C.
Braun-Pivet
Braun-Pivet is the surname of Yaël Braun-Pivet, a prominent French politician who has served as President of the National Assembly.
-
D.
Gamo
Gamo is an Omotic language spoken primarily by the Gamo people in southwestern Ethiopia.
-
E.
Mermoz
Mermoz is a residential neighborhood in Lyon, France, known for its post-war urban development and diverse population within the city’s 8th arrondissement.
- 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: Pelikan Triple: [Jaroslav Pelikan, familyName, Pelikan]
Generated description
Pelikan is a surname of Slavic origin borne by various notable individuals, including scholars and public figures.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pelikan Target entity description: Pelikan is a surname of Slavic origin borne by various notable individuals, including scholars and public figures.
-
A.
Magura
Magura is a town and district headquarters in southwestern Bangladesh known for its agricultural surroundings and location within the Khulna Division.
-
B.
Magura
Magura is a mountain peak in the Kysucké Beskydy range of northern Slovakia, known for its forested slopes and scenic hiking routes.
-
C.
Braun-Pivet
Braun-Pivet is the surname of Yaël Braun-Pivet, a prominent French politician who has served as President of the National Assembly.
-
D.
Gamo
Gamo is an Omotic language spoken primarily by the Gamo people in southwestern Ethiopia.
-
E.
Mermoz
Mermoz is a residential neighborhood in Lyon, France, known for its post-war urban development and diverse population within the city’s 8th arrondissement.
- 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_69e11e5445bc8190b6a9481926db3355 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15cb0dfb88190a4175e5e95d7ad4b |
completed | April 29, 2026, 1:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0b17dfe7f48190a0879581d3e4d80f |
completed | May 18, 2026, 1:45 p.m. |
| NEDg | Description generation | batch_6a0b18d9beec8190b890e127c62b2ef6 |
completed | May 18, 2026, 1:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0b19953e248190b599854dc58771a0 |
completed | May 18, 2026, 1:52 p.m. |
Created at: April 16, 2026, 8:49 p.m.