Triple
T12615801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Brody (1941) |
E301248
|
entity |
| Predicate | location |
P40
|
FINISHED |
| Object |
Brody
Brody is a historic town in western Ukraine that has long served as a strategic military and trade crossroads in the region.
|
E992045
|
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: Brody | Statement: [Battle of Brody (1941), location, Brody]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brody Context triple: [Battle of Brody (1941), location, Brody]
-
A.
Brody
Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
-
B.
Brody Bruce
Brody Bruce is a comic book–obsessed slacker and central character from Kevin Smith’s film "Mallrats," known for his sarcastic wit and pop-culture rants.
-
C.
Braeden
Braeden is the given first name of NHL player Brady Tkachuk, a prominent American-born Canadian ice hockey forward.
-
D.
Brayden
Brayden is a masculine given name commonly used in English-speaking countries, often associated with modern, trendy baby naming styles.
-
E.
Brody Duke
Brody Duke was an American tobacco industrialist and member of the prominent Duke family that helped shape the tobacco industry in the late 19th century.
- 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: Brody Triple: [Battle of Brody (1941), location, Brody]
Generated description
Brody is a historic town in western Ukraine that has long served as a strategic military and trade crossroads in the region.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brody Target entity description: Brody is a historic town in western Ukraine that has long served as a strategic military and trade crossroads in the region.
-
A.
Brody
Brody is a surname of English and Irish origin borne by various notable individuals across fields such as entertainment, sports, and public life.
-
B.
Brody Bruce
Brody Bruce is a comic book–obsessed slacker and central character from Kevin Smith’s film "Mallrats," known for his sarcastic wit and pop-culture rants.
-
C.
Braeden
Braeden is the given first name of NHL player Brady Tkachuk, a prominent American-born Canadian ice hockey forward.
-
D.
Brayden
Brayden is a masculine given name commonly used in English-speaking countries, often associated with modern, trendy baby naming styles.
-
E.
Brody Duke
Brody Duke was an American tobacco industrialist and member of the prominent Duke family that helped shape the tobacco industry in the late 19th century.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d960c4f5b48190af76414ef678ba7c |
completed | April 10, 2026, 8:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ed2e12c819097cfd2a40116f491 |
completed | May 2, 2026, 8:30 p.m. |
| NEDg | Description generation | batch_69f65fb03b248190b264230b84b17635 |
completed | May 2, 2026, 8:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6608ec32c8190803c6f5677c300d6 |
completed | May 2, 2026, 8:37 p.m. |
Created at: April 9, 2026, 5:12 p.m.