Triple
T11155002
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theodore Dwight Weld |
E263883
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Weld
Weld is a surname of English origin borne by various notable individuals, including American abolitionist Theodore Dwight Weld.
|
E908531
|
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: Weld | Statement: [Theodore Dwight Weld, familyName, Weld]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Weld Context triple: [Theodore Dwight Weld, familyName, Weld]
-
A.
Weld
Weld is a live album by Neil Young and Crazy Horse, renowned for its intense, feedback-heavy performances of his rock classics.
-
B.
Weld
Weld is a farming simulation game in the Harvest Moon series that precedes the installment titled Harvest Moon.
-
C.
Weld
Weld is an American actress known for her work in film and television from the 1950s through the 1990s, including acclaimed performances in movies like "Play It As It Lays" and "Looking for Mr. Goodbar."
-
D.
Bessemer
Bessemer is a surname most notably associated with Sir Henry Bessemer, the English inventor who revolutionized steel production in the 19th century.
-
E.
Bessemer
Bessemer is an industrial city in Jefferson County, Alabama, historically known for its steelmaking and manufacturing.
- 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: Weld Triple: [Theodore Dwight Weld, familyName, Weld]
Generated description
Weld is a surname of English origin borne by various notable individuals, including American abolitionist Theodore Dwight Weld.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Weld Target entity description: Weld is a surname of English origin borne by various notable individuals, including American abolitionist Theodore Dwight Weld.
-
A.
Weld
Weld is a live album by Neil Young and Crazy Horse, renowned for its intense, feedback-heavy performances of his rock classics.
-
B.
Weld
Weld is a farming simulation game in the Harvest Moon series that precedes the installment titled Harvest Moon.
-
C.
Weld
Weld is an American actress known for her work in film and television from the 1950s through the 1990s, including acclaimed performances in movies like "Play It As It Lays" and "Looking for Mr. Goodbar."
-
D.
Bessemer
Bessemer is a surname most notably associated with Sir Henry Bessemer, the English inventor who revolutionized steel production in the 19th century.
-
E.
Bessemer
Bessemer is an industrial city in Jefferson County, Alabama, historically known for its steelmaking and manufacturing.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8741cd48190b7cc29c6b6bc54ff |
completed | April 9, 2026, 5:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e46341f224819099dd618b377e5bc2 |
completed | April 19, 2026, 5:08 a.m. |
| NEDg | Description generation | batch_69e46c3448348190b2c062d21771066d |
completed | April 19, 2026, 5:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e46dadbc5c8190b41279a05731dc95 |
completed | April 19, 2026, 5:52 a.m. |
Created at: April 8, 2026, 9:28 p.m.