Triple
T19187626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcides Escobar |
E469745
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
Esky
Esky is the nickname of Alcides Escobar, a Venezuelan professional baseball shortstop best known for his defensive prowess and key role in the Kansas City Royals’ 2015 World Series championship.
|
E1363021
|
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: Esky | Statement: [Alcides Escobar, nickname, Esky]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Esky Context triple: [Alcides Escobar, nickname, Esky]
-
A.
The Cooler
The Cooler is a 2003 romantic drama film set in a Las Vegas casino, best known for its blend of noir atmosphere and character-driven storytelling.
-
B.
Tumbler
Tumbler was a series of early 1950s U.S. nuclear weapons tests conducted at the Nevada Test Site to study blast and radiation effects.
-
C.
Tumbler
Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
-
D.
Omni-Freeze
Omni-Freeze is a Columbia Sportswear cooling fabric technology designed to help keep the wearer cooler and more comfortable in hot conditions.
-
E.
Bottle
Bottle is a lightweight Python web framework used for building simple web applications and APIs in a single file.
- 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: Esky Triple: [Alcides Escobar, nickname, Esky]
Generated description
Esky is the nickname of Alcides Escobar, a Venezuelan professional baseball shortstop best known for his defensive prowess and key role in the Kansas City Royals’ 2015 World Series championship.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Esky Target entity description: Esky is the nickname of Alcides Escobar, a Venezuelan professional baseball shortstop best known for his defensive prowess and key role in the Kansas City Royals’ 2015 World Series championship.
-
A.
The Cooler
The Cooler is a 2003 romantic drama film set in a Las Vegas casino, best known for its blend of noir atmosphere and character-driven storytelling.
-
B.
Tumbler
Tumbler is a close associate and ally of master car thief Memphis Raines in the action film "Gone in 60 Seconds."
-
C.
Tumbler
Tumbler was a series of early 1950s U.S. nuclear weapons tests conducted at the Nevada Test Site to study blast and radiation effects.
-
D.
Omni-Freeze
Omni-Freeze is a Columbia Sportswear cooling fabric technology designed to help keep the wearer cooler and more comfortable in hot conditions.
-
E.
Bottle
Bottle is a lightweight Python web framework used for building simple web applications and APIs in a single file.
- 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f89f3ebc8190ba01ae075ffc77df |
completed | April 20, 2026, 9:57 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a06f8ba0a508190af6adb8ff3b8969e |
completed | May 15, 2026, 10:43 a.m. |
| NEDg | Description generation | batch_6a06f987d3e88190ade6412afd3e1426 |
completed | May 15, 2026, 10:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a06fa6c6e5481909beb3a33517264f3 |
completed | May 15, 2026, 10:50 a.m. |
Created at: April 10, 2026, 12:07 p.m.