Triple
T10189063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Waverly Gallery |
E237984
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Howard
Howard is a character in Kenneth Lonergan's play "The Waverly Gallery," serving as a key figure in the story's exploration of family, memory, and aging.
|
E846759
|
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: Howard | Statement: [The Waverly Gallery, character, Howard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Howard Context triple: [The Waverly Gallery, character, Howard]
-
A.
Howard
Howard is the given name of the influential American film director, producer, and screenwriter Howard Hawks.
-
B.
Howard
Howard is a common English surname shared by numerous notable figures across entertainment, politics, and other fields.
-
C.
Howard
Howard is the middle name of William Howard Taft, the 27th president of the United States and later Chief Justice of the Supreme Court.
-
D.
Howard
Howard is a masculine given name of Old English origin meaning "high guardian" or "noble watchman," borne by numerous notable figures across politics, arts, and academia.
-
E.
Howard
Howard is one of Sethe’s sons in Toni Morrison’s novel "Beloved," a child whose life is shaped by the trauma and legacy of slavery.
- 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: Howard Triple: [The Waverly Gallery, character, Howard]
Generated description
Howard is a character in Kenneth Lonergan's play "The Waverly Gallery," serving as a key figure in the story's exploration of family, memory, and aging.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Howard Target entity description: Howard is a character in Kenneth Lonergan's play "The Waverly Gallery," serving as a key figure in the story's exploration of family, memory, and aging.
-
A.
Howard
Howard is a young boy who serves as a minor but symbolically important character in the play "Inherit the Wind," representing the town’s impressionable youth amid the evolution-versus-creationism trial.
-
B.
Howard
Howard is one of Sethe’s sons in Toni Morrison’s novel "Beloved," a child whose life is shaped by the trauma and legacy of slavery.
-
C.
Howard
Howard is a fictional character best known as the romantic interest of Marina in their shared narrative.
-
D.
Howard
Howard is a seasoned, wise old prospector in the classic 1948 film "The Treasure of the Sierra Madre," known for his experience, moral insight, and pivotal role in the gold-hunting expedition.
-
E.
Howard
Howard is a common English surname shared by numerous notable figures across entertainment, politics, and other fields.
- 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_69ca84de1b208190bf17bb305b002605 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded7c3278819093312665b54d888c |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317b734a4819085645caea8ba0481 |
completed | April 6, 2026, 2:17 a.m. |
| NEDg | Description generation | batch_69d319937ec08190bf5442a7e3a9ba9f |
completed | April 6, 2026, 2:25 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d31a39d73481908cf5713205f910fb |
completed | April 6, 2026, 2:28 a.m. |
Created at: March 30, 2026, 9:12 p.m.