Triple
T22977485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finnick Odair |
E571365
|
entity |
| Predicate | mentor |
P3665
|
FINISHED |
| Object |
Mags
Mags is an elderly former Hunger Games victor from District 4 who serves as a mentor and tribute in Suzanne Collins’ "Catching Fire."
|
E1564798
|
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: Mags | Statement: [Finnick Odair, mentor, Mags]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mags Context triple: [Finnick Odair, mentor, Mags]
-
A.
Mags
Mags is a common diminutive or nickname for the given name Madeleine.
-
B.
Magazeen
Magazeen is a dancehall and reggae artist known for his affiliation with Rick Ross’s Maybach Music Group.
-
C.
Magazia
Magazia is a small village on the Greek island of Paxos, known for its traditional character and tranquil, rural setting.
-
D.
Maggie-Now
Maggie-Now is a novel by American author Betty Smith, best known for its portrayal of Irish-American family life in early 20th-century Brooklyn.
-
E.
Magan
Magan was an ancient Bronze Age region, likely in present-day Oman or the surrounding Arabian Peninsula, known as a key maritime trading partner of the Indus Valley Civilization and Mesopotamia.
- 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: Mags Triple: [Finnick Odair, mentor, Mags]
Generated description
Mags is an elderly former Hunger Games victor from District 4 who serves as a mentor and tribute in Suzanne Collins’ "Catching Fire."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mags Target entity description: Mags is an elderly former Hunger Games victor from District 4 who serves as a mentor and tribute in Suzanne Collins’ "Catching Fire."
-
A.
Mags
Mags is a common diminutive or nickname for the given name Madeleine.
-
B.
Magazeen
Magazeen is a dancehall and reggae artist known for his affiliation with Rick Ross’s Maybach Music Group.
-
C.
Magazia
Magazia is a small village on the Greek island of Paxos, known for its traditional character and tranquil, rural setting.
-
D.
Maggie-Now
Maggie-Now is a novel by American author Betty Smith, best known for its portrayal of Irish-American family life in early 20th-century Brooklyn.
-
E.
Magan
Magan was an ancient Bronze Age region, likely in present-day Oman or the surrounding Arabian Peninsula, known as a key maritime trading partner of the Indus Valley Civilization and Mesopotamia.
- 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_69e245b3c50481908bb3741ec9f40862 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18292f3788190ab4e9d559e0070c8 |
completed | April 29, 2026, 4:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bd36f73a48190ba07a754949e2e40 |
completed | May 19, 2026, 3:05 a.m. |
| NEDg | Description generation | batch_6a0bd41c89708190a3df2a798ca25c99 |
completed | May 19, 2026, 3:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bd5263734819082ce8b1c3082243f |
completed | May 19, 2026, 3:12 a.m. |
Created at: April 17, 2026, 3:48 p.m.