Triple
T7642160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andor |
E173033
|
entity |
| Predicate | featuresCharacter |
P626
|
FINISHED |
| Object |
Vel Sartha
Vel Sartha is a rebel operative and key member of the nascent Rebellion in the Star Wars series "Andor," known for leading a pivotal mission against the Empire.
|
E680080
|
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: Vel Sartha | Statement: [Andor, featuresCharacter, Vel Sartha]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vel Sartha Context triple: [Andor, featuresCharacter, Vel Sartha]
-
A.
Berriane
Berriane is a town in Algeria known as part of the historic M’zab oasis region, characterized by its traditional architecture and Saharan environment.
-
B.
Levasy
Levasy is a small city located in Jackson County in the U.S. state of Missouri.
-
C.
Temara
Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
-
D.
Laghée
Laghée is a regional variety of the Lombard language traditionally spoken around Lake Como in northern Italy.
-
E.
Lasbela
Lasbela is a coastal district and city in Pakistan’s Balochistan province, known for its strategic location near Karachi and its mix of industrial, agricultural, and fishing activities.
- 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: Vel Sartha Triple: [Andor, featuresCharacter, Vel Sartha]
Generated description
Vel Sartha is a rebel operative and key member of the nascent Rebellion in the Star Wars series "Andor," known for leading a pivotal mission against the Empire.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vel Sartha Target entity description: Vel Sartha is a rebel operative and key member of the nascent Rebellion in the Star Wars series "Andor," known for leading a pivotal mission against the Empire.
-
A.
Berriane
Berriane is a town in Algeria known as part of the historic M’zab oasis region, characterized by its traditional architecture and Saharan environment.
-
B.
Levasy
Levasy is a small city located in Jackson County in the U.S. state of Missouri.
-
C.
Temara
Temara is a coastal city in northwestern Morocco, situated just south of Rabat and known for its beaches and growing residential and industrial areas.
-
D.
Laghée
Laghée is a regional variety of the Lombard language traditionally spoken around Lake Como in northern Italy.
-
E.
Lasbela
Lasbela is a coastal district and city in Pakistan’s Balochistan province, known for its strategic location near Karachi and its mix of industrial, agricultural, and fishing activities.
- 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_69c6995360188190968ee57b72a1627f |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facefbe08190882bd76cf3cd605e |
completed | March 27, 2026, 9:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c89acaac6481908ef763647a0ca9b3 |
completed | March 29, 2026, 3:21 a.m. |
| NEDg | Description generation | batch_69c89e96b6a08190ba490b79aa0ce366 |
completed | March 29, 2026, 3:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c89ee8b7d88190bf6439cdc471e5b6 |
completed | March 29, 2026, 3:39 a.m. |
Created at: March 27, 2026, 3:58 p.m.