Triple
T3549687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dakota Fanning |
E75080
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Hannah
Hannah is an alternate given name associated with American actress Dakota Fanning, whose full name is Hannah Dakota Fanning.
|
E367987
|
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: Hannah | Statement: [Dakota Fanning, givenName, Hannah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannah Context triple: [Dakota Fanning, givenName, Hannah]
-
A.
Hannah
Hannah is a biblical figure in the Book of 1 Samuel known for her fervent prayer for a child and as the mother of the prophet Samuel.
-
B.
Hannah
Hannah is a person associated in some way with the city of Santa Ana, California.
-
C.
Hannah
Hannah is a compassionate Jewish laundress and the love interest of the Jewish Barber in Charlie Chaplin’s 1940 satirical film "The Great Dictator."
-
D.
Hannah
Hannah is a key survivor character in the British post-apocalyptic horror film "28 Days Later," known for her resilience and resourcefulness amid a rage virus outbreak in London.
-
E.
Hannah Peace
Hannah Peace is a free-spirited, sensual, and unconventional woman in Toni Morrison’s novel "Sula," known for her complex relationship with her daughter and her defiance of traditional social norms.
- 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: Hannah Triple: [Dakota Fanning, givenName, Hannah]
Generated description
Hannah is an alternate given name associated with American actress Dakota Fanning, whose full name is Hannah Dakota Fanning.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hannah Target entity description: Hannah is an alternate given name associated with American actress Dakota Fanning, whose full name is Hannah Dakota Fanning.
-
A.
Hannah
Hannah is a biblical figure in the Book of 1 Samuel known for her fervent prayer for a child and as the mother of the prophet Samuel.
-
B.
Hannah
Hannah is a person associated in some way with the city of Santa Ana, California.
-
C.
Hannah
Hannah is a compassionate Jewish laundress and the love interest of the Jewish Barber in Charlie Chaplin’s 1940 satirical film "The Great Dictator."
-
D.
Hannah
Hannah is a key survivor character in the British post-apocalyptic horror film "28 Days Later," known for her resilience and resourcefulness amid a rage virus outbreak in London.
-
E.
Hannah Peace
Hannah Peace is a free-spirited, sensual, and unconventional woman in Toni Morrison’s novel "Sula," known for her complex relationship with her daughter and her defiance of traditional social norms.
- 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_69ad85d33c6c819081d5ac1df13b5680 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbfd38c8c8190a4591689ad57c998 |
completed | March 8, 2026, 6:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38be9335c81909ba546a079134c8f |
completed | March 13, 2026, 4 a.m. |
| NEDg | Description generation | batch_69b38c5cfb608190b451be14246d5481 |
completed | March 13, 2026, 4:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b38ce0e1688190a7ee3d079fb83f3d |
completed | March 13, 2026, 4:04 a.m. |
Created at: March 8, 2026, 3:20 p.m.