Triple
T8945542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Luke, Maryland |
E213211
|
entity |
| Predicate | hasName |
P744
|
FINISHED |
| Object |
Luke
Luke is a small town located in Allegany County, Maryland, known historically for its paper mill industry.
|
E768001
|
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: Luke | Statement: [Luke, Maryland, hasName, Luke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luke Context triple: [Luke, Maryland, hasName, Luke]
-
A.
Luke
Luke is a character portrayed by Chiwetel Ejiofor in the romantic comedy film "Love Actually."
-
B.
Luke
Luke is a central character in James Baldwin’s play "The Amen Corner," serving as the estranged husband whose return forces the protagonist and her church community to confront painful truths about faith, family, and hypocrisy.
-
C.
Luke
Luke is traditionally regarded as the author of the Gospel of Luke and the Acts of the Apostles in the New Testament, and is thought to have been a physician and companion of the Apostle Paul.
-
D.
Luke
Luke is the central protagonist of the film "Wicker Park," whose obsessive search for a lost love drives the movie’s romantic mystery plot.
-
E.
Jake
Jake is a fictional character from the "Pacific Rim" film franchise, known as the charismatic Jaeger pilot and son of legendary pilot Stacker Pentecost.
- 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: Luke Triple: [Luke, Maryland, hasName, Luke]
Generated description
Luke is a small town located in Allegany County, Maryland, known historically for its paper mill industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Luke Target entity description: Luke is a small town located in Allegany County, Maryland, known historically for its paper mill industry.
-
A.
Luke
Luke is traditionally regarded as the author of the Gospel of Luke and the Acts of the Apostles in the New Testament, and is thought to have been a physician and companion of the Apostle Paul.
-
B.
Luke
Luke is a character portrayed by Chiwetel Ejiofor in the romantic comedy film "Love Actually."
-
C.
Luke
Luke is the central protagonist of the film "Wicker Park," whose obsessive search for a lost love drives the movie’s romantic mystery plot.
-
D.
Luke
Luke is a central character in James Baldwin’s play "The Amen Corner," serving as the estranged husband whose return forces the protagonist and her church community to confront painful truths about faith, family, and hypocrisy.
-
E.
Jake
Jake is a fictional character from the "Pacific Rim" film franchise, known as the charismatic Jaeger pilot and son of legendary pilot Stacker Pentecost.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66db998c8190999a7a686bbdda1f |
completed | April 1, 2026, 12:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc1fcb44481908324220aeba1f4e2 |
completed | April 3, 2026, 1:34 p.m. |
| NEDg | Description generation | batch_69cfc31798ec81908c200dd17be5e785 |
completed | April 3, 2026, 1:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfc44441208190a6b588c0609511fb |
completed | April 3, 2026, 1:44 p.m. |
Created at: March 30, 2026, 6:59 p.m.